import sys
!{sys.executable} -m pip install -U pandas-profiling
import os
#Built-in
import time
import warnings
import statsmodels
import numpy as np
import pandas as pd
from datetime import datetime
#Visualization
from tqdm import tqdm
import seaborn as sns
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import plotly.graph_objects as go
#Dimensionality Reduction
import umap
import prince
#EDA Libraries
from pandas_profiling import ProfileReport
#MICE Libraries
from sklearn.experimental import enable_iterative_imputer
from sklearn.impute import IterativeImputer
#Distribution Normalization
from sklearn.preprocessing import OrdinalEncoder, PowerTransformer, QuantileTransformer, StandardScaler
from statsmodels.api import qqplot
import sklearn.covariance as cov
from scipy.stats import chi2
#PCA
from sklearn.decomposition import PCA
#Clustering & Visualization Libraries
import sklearn.cluster as cluster
from sklearn.cluster import KMeans
from kmodes.kprototypes import KPrototypes
from sklearn.cluster import AgglomerativeClustering
from scipy.cluster.hierarchy import dendrogram, linkage, set_link_color_palette
from yellowbrick.cluster import KElbowVisualizer, SilhouetteVisualizer, silhouette_visualizer, InterclusterDistance
from yellowbrick.cluster.elbow import kelbow_visualizer
from sklearn.mixture import GaussianMixture
from sklearn.cluster import DBSCAN
#Clustering Metrics
from sklearn.metrics import silhouette_score, silhouette_samples, calinski_harabasz_score, davies_bouldin_score
#ML Prediction
import shap
from lightgbm import LGBMClassifier
from sklearn.model_selection import cross_val_score
warnings.filterwarnings('ignore')
%config InlineBackend.figure_format = 'retina'
recalculate = False # False -> Read pickle dumps, True -> Recalculate all the values
# Data Loading
data = pd.read_csv(os.path.join(os.getcwd(),'Data/donors.csv'),low_memory=False)
data.drop(data.columns[0],inplace=True,axis=1)
sns.set_style('white')
#Check duplicates
print('No duplicates' if not any(data.duplicated()) else 'Duplicates are found')
No duplicates
#set random state
random_state=np.random.RandomState(5)
#Check for data type of columns
data.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 95412 entries, 0 to 95411 Columns: 475 entries, ODATEDW to GEOCODE2 dtypes: float64(49), int64(301), object(125) memory usage: 345.8+ MB
# describe columns with object dtype
pd.set_option('display.max_columns', None)
data.describe(include='all')
| ODATEDW | OSOURCE | TCODE | STATE | ZIP | MAILCODE | PVASTATE | DOB | NOEXCH | RECINHSE | RECP3 | RECPGVG | RECSWEEP | MDMAUD | DOMAIN | HOMEOWNR | CHILD03 | CHILD07 | CHILD12 | CHILD18 | NUMCHLD | INCOME | GENDER | WEALTH1 | HIT | MBCRAFT | MBGARDEN | MBBOOKS | MBCOLECT | MAGFAML | MAGFEM | MAGMALE | PUBGARDN | PUBCULIN | PUBHLTH | PUBDOITY | PUBNEWFN | PUBPHOTO | PUBOPP | DATASRCE | MALEMILI | MALEVET | VIETVETS | WWIIVETS | LOCALGOV | STATEGOV | FEDGOV | SOLP3 | SOLIH | MAJOR | WEALTH2 | GEOCODE | COLLECT1 | VETERANS | BIBLE | CATLG | HOMEE | PETS | CDPLAY | STEREO | PCOWNERS | PHOTO | CRAFTS | FISHER | GARDENIN | BOATS | WALKER | KIDSTUFF | CARDS | PLATES | LIFESRC | PEPSTRFL | POP901 | POP902 | POP903 | POP90C1 | POP90C2 | POP90C3 | POP90C4 | POP90C5 | ETH1 | ETH2 | ETH3 | ETH4 | ETH5 | ETH6 | ETH7 | ETH8 | ETH9 | ETH10 | ETH11 | ETH12 | ETH13 | ETH14 | ETH15 | ETH16 | AGE901 | AGE902 | AGE903 | AGE904 | AGE905 | AGE906 | AGE907 | CHIL1 | CHIL2 | CHIL3 | AGEC1 | AGEC2 | AGEC3 | AGEC4 | AGEC5 | AGEC6 | AGEC7 | CHILC1 | CHILC2 | CHILC3 | CHILC4 | CHILC5 | HHAGE1 | HHAGE2 | HHAGE3 | HHN1 | HHN2 | HHN3 | HHN4 | HHN5 | HHN6 | MARR1 | MARR2 | MARR3 | MARR4 | HHP1 | HHP2 | DW1 | DW2 | DW3 | DW4 | DW5 | DW6 | DW7 | DW8 | DW9 | HV1 | HV2 | HV3 | HV4 | HU1 | HU2 | HU3 | HU4 | HU5 | HHD1 | HHD2 | HHD3 | HHD4 | HHD5 | HHD6 | HHD7 | HHD8 | HHD9 | HHD10 | HHD11 | HHD12 | ETHC1 | ETHC2 | ETHC3 | ETHC4 | ETHC5 | ETHC6 | HVP1 | HVP2 | HVP3 | HVP4 | HVP5 | HVP6 | HUR1 | HUR2 | RHP1 | RHP2 | RHP3 | RHP4 | HUPA1 | HUPA2 | HUPA3 | HUPA4 | HUPA5 | HUPA6 | HUPA7 | RP1 | RP2 | RP3 | RP4 | MSA | ADI | DMA | IC1 | IC2 | IC3 | IC4 | IC5 | IC6 | IC7 | IC8 | IC9 | IC10 | IC11 | IC12 | IC13 | IC14 | IC15 | IC16 | IC17 | IC18 | IC19 | IC20 | IC21 | IC22 | IC23 | HHAS1 | HHAS2 | HHAS3 | HHAS4 | MC1 | MC2 | MC3 | TPE1 | TPE2 | TPE3 | TPE4 | TPE5 | TPE6 | TPE7 | TPE8 | TPE9 | PEC1 | PEC2 | TPE10 | TPE11 | TPE12 | TPE13 | LFC1 | LFC2 | LFC3 | LFC4 | LFC5 | LFC6 | LFC7 | LFC8 | LFC9 | LFC10 | OCC1 | OCC2 | OCC3 | OCC4 | OCC5 | OCC6 | OCC7 | OCC8 | OCC9 | OCC10 | OCC11 | OCC12 | OCC13 | EIC1 | EIC2 | EIC3 | EIC4 | EIC5 | EIC6 | EIC7 | EIC8 | EIC9 | EIC10 | EIC11 | EIC12 | EIC13 | EIC14 | EIC15 | EIC16 | OEDC1 | OEDC2 | OEDC3 | OEDC4 | OEDC5 | OEDC6 | OEDC7 | EC1 | EC2 | EC3 | EC4 | EC5 | EC6 | EC7 | EC8 | SEC1 | SEC2 | SEC3 | SEC4 | SEC5 | AFC1 | AFC2 | AFC3 | AFC4 | AFC5 | AFC6 | VC1 | VC2 | VC3 | VC4 | ANC1 | ANC2 | ANC3 | ANC4 | ANC5 | ANC6 | ANC7 | ANC8 | ANC9 | ANC10 | ANC11 | ANC12 | ANC13 | ANC14 | ANC15 | POBC1 | POBC2 | LSC1 | LSC2 | LSC3 | LSC4 | VOC1 | VOC2 | VOC3 | HC1 | HC2 | HC3 | HC4 | HC5 | HC6 | HC7 | HC8 | HC9 | HC10 | HC11 | HC12 | HC13 | HC14 | HC15 | HC16 | HC17 | HC18 | HC19 | HC20 | HC21 | MHUC1 | MHUC2 | AC1 | AC2 | ADATE_2 | ADATE_3 | ADATE_4 | ADATE_5 | ADATE_6 | ADATE_7 | ADATE_8 | ADATE_9 | ADATE_10 | ADATE_11 | ADATE_12 | ADATE_13 | ADATE_14 | ADATE_15 | ADATE_16 | ADATE_17 | ADATE_18 | ADATE_19 | ADATE_20 | ADATE_21 | ADATE_22 | ADATE_23 | ADATE_24 | RFA_2 | RFA_3 | RFA_4 | RFA_5 | RFA_6 | RFA_7 | RFA_8 | RFA_9 | RFA_10 | RFA_11 | RFA_12 | RFA_13 | RFA_14 | RFA_15 | RFA_16 | RFA_17 | RFA_18 | RFA_19 | RFA_20 | RFA_21 | RFA_22 | RFA_23 | RFA_24 | CARDPROM | MAXADATE | NUMPROM | CARDPM12 | NUMPRM12 | RDATE_3 | RDATE_4 | RDATE_5 | RDATE_6 | RDATE_7 | RDATE_8 | RDATE_9 | RDATE_10 | RDATE_11 | RDATE_12 | RDATE_13 | RDATE_14 | RDATE_15 | RDATE_16 | RDATE_17 | RDATE_18 | RDATE_19 | RDATE_20 | RDATE_21 | RDATE_22 | RDATE_23 | RDATE_24 | RAMNT_3 | RAMNT_4 | RAMNT_5 | RAMNT_6 | RAMNT_7 | RAMNT_8 | RAMNT_9 | RAMNT_10 | RAMNT_11 | RAMNT_12 | RAMNT_13 | RAMNT_14 | RAMNT_15 | RAMNT_16 | RAMNT_17 | RAMNT_18 | RAMNT_19 | RAMNT_20 | RAMNT_21 | RAMNT_22 | RAMNT_23 | RAMNT_24 | RAMNTALL | NGIFTALL | CARDGIFT | MINRAMNT | MINRDATE | MAXRAMNT | MAXRDATE | LASTGIFT | LASTDATE | FISTDATE | NEXTDATE | TIMELAG | AVGGIFT | CONTROLN | HPHONE_D | RFA_2R | RFA_2F | RFA_2A | MDMAUD_R | MDMAUD_F | MDMAUD_A | GEOCODE2 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| count | 95412 | 95412 | 95412.000000 | 95412 | 95412 | 95412 | 95412 | 71529 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 12386.000000 | 74126.000000 | 95412 | 50680.000000 | 95412.000000 | 42558.000000 | 42558.000000 | 42558.000000 | 42498.000000 | 42558.000000 | 42558.000000 | 42558.000000 | 42558.000000 | 42558.000000 | 42558.000000 | 42558.000000 | 42558.000000 | 42558.000000 | 42558.000000 | 95412 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412 | 95412 | 95412 | 51589.000000 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 95412.000000 | 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| unique | 54 | 896 | NaN | 57 | 19938 | 2 | 3 | 847 | 4 | 2 | 2 | 2 | 2 | 28 | 17 | 3 | 4 | 4 | 4 | 4 | NaN | NaN | 7 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 4 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 5 | 8 | 2 | NaN | 8 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 4 | 2 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 2 | 2 | 8 | 1 | 2 | 3 | 5 | 3 | 2 | 4 | 4 | 3 | 2 | 1 | 3 | 3 | 9 | 3 | 2 | 2 | 5 | 3 | 2 | 14 | 71 | 64 | 41 | 109 | 106 | 109 | 107 | 94 | 101 | 107 | 87 | 95 | 34 | 123 | 118 | 122 | 108 | 80 | 102 | 117 | 87 | 97 | NaN | 5 | NaN | NaN | NaN | 14 | 21 | 5 | 17 | 9 | 14 | 10 | 8 | 12 | 10 | 14 | 12 | 16 | 18 | 11 | 14 | 13 | 10 | 12 | 13 | 17 | 14 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 146 | NaN | 150 | NaN | 24 | 176 | 188 | NaN | NaN | NaN | NaN | 1 | NaN | 4 | 5 | 4 | 5 | 5 |
| top | 2015-01-01 | MBC | NaN | CA | 85351 | 1968-01-01 | 0 | XXXX | R2 | H | NaN | NaN | F | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 3 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 2017-06-01 | 2016-06-01 | 2016-04-01 | 2016-04-01 | 2016-03-01 | 2016-02-01 | 2016-01-01 | 2015-11-01 | 2015-10-01 | 2015-10-01 | 2015-08-01 | 2015-07-01 | 2015-06-01 | 2015-04-01 | 2015-03-01 | 2015-02-01 | 2015-01-01 | 2014-11-01 | 2014-11-01 | 2014-10-01 | 2014-09-01 | 2014-07-01 | 2014-06-01 | L1F | A1F | A1F | A1F | A1F | A1F | A1F | NaN | 2017-02-01 | NaN | NaN | NaN | 2016-06-01 | 2016-05-01 | 2017-03-01 | 2016-03-01 | 2016-03-01 | 2016-01-01 | 2015-12-01 | 2015-11-01 | 2015-11-01 | 2015-09-01 | 2015-08-01 | 2015-06-01 | 2015-05-01 | 2015-04-01 | 2015-03-01 | 2015-01-01 | 2014-12-01 | 2014-12-01 | 2014-11-01 | 2014-09-01 | 2014-08-01 | 2014-07-01 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 2016-02-01 | NaN | 2015-12-01 | NaN | 2015-12-01 | 2015-01-01 | 2015-04-01 | NaN | NaN | NaN | NaN | L | NaN | F | X | X | X | A | ||||||||||||||||||||||||||||||||||||||||||||||||||
| freq | 15358 | 4539 | NaN | 17343 | 61 | 94013 | 93954 | 1479 | 95085 | 88709 | 93395 | 95298 | 93795 | 95118 | 13623 | 52354 | 94266 | 93846 | 93601 | 92565 | NaN | NaN | 51277 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 43549 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 95232 | 89212 | 95118 | NaN | 80168 | 90210 | 84986 | 86541 | 87547 | 94525 | 81086 | 83158 | 82618 | 84931 | 90626 | 87236 | 88282 | 82010 | 93384 | 84911 | 93876 | 94371 | 94852 | 54032 | 50143 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 95399 | 93444 | 92405 | 61822 | 91804 | 81512 | 85468 | 80718 | 57562 | 58631 | 49299 | 54713 | 76381 | 29935 | 73422 | 62326 | 43453 | 69304 | 45198 | 55865 | 63908 | 38877 | 58161 | 30380 | 21950 | 21818 | 33590 | 15696 | 10954 | 11312 | 11245 | 32748 | 10422 | 9857 | 40219 | 18867 | 65477 | 20417 | 27650 | 21263 | 24492 | 50200 | 35212 | 25648 | 56274 | 36973 | NaN | 95014 | NaN | NaN | NaN | 105 | 86 | 3 | 575 | 6494 | 10209 | 13290 | 5471 | 7010 | 13496 | 7396 | 13533 | 4862 | 16670 | 4729 | 10665 | 12504 | 4516 | 5006 | 11195 | 4522 | 7861 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 3041 | NaN | 10563 | NaN | 19896 | 2957 | 2253 | NaN | NaN | NaN | NaN | 95412 | NaN | 46964 | 95118 | 95118 | 95118 | 34484 |
| mean | NaN | NaN | 54.223117 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 1.527773 | 3.886248 | NaN | 5.345699 | 3.321438 | 0.152075 | 0.059166 | 1.116382 | 0.063932 | 0.448329 | 0.126322 | 0.065722 | 0.141806 | 0.145237 | 0.714484 | 0.237723 | 0.376239 | 0.005874 | 0.237558 | NaN | 1.048443 | 30.445332 | 29.702312 | 32.637719 | 6.842326 | 4.568566 | 3.110867 | NaN | NaN | NaN | 4.954525 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 3255.880204 | 864.993083 | 1222.573460 | 58.589653 | 13.622479 | 26.140527 | 48.211724 | 50.951390 | 84.854505 | 7.467405 | 0.776904 | 2.905704 | 7.458077 | 0.216011 | 0.397350 | 0.612806 | 0.561491 | 0.250587 | 0.210309 | 0.068388 | 5.138169 | 0.302478 | 0.327433 | 1.513615 | 34.475276 | 41.911321 | 45.108645 | 35.917379 | 44.694231 | 47.889437 | 24.515092 | 39.592745 | 38.357638 | 21.014715 | 12.196873 | 22.189819 | 20.652979 | 14.057781 | 11.857785 | 10.543275 | 7.667966 | 16.175659 | 16.139427 | 31.634648 | 19.754171 | 15.256854 | 24.603289 | 9.37184 | 22.308473 | 22.821710 | 33.630445 | 42.697428 | 25.615415 | 10.471020 | 3.896460 | 58.100616 | 10.693351 | 7.424695 | 22.948424 | 185.271737 | 259.684998 | 70.083532 | 66.036599 | 2.900862 | 19.480778 | 16.555402 | 13.102922 | 1.789848 | 1.160315 | 0.621201 | 1061.838238 | 1133.031086 | 4.224249 | 3.875886 | 69.696831 | 29.445772 | 89.966608 | 9.176477 | 13.737276 | 35.65453 | 71.503899 | 58.755052 | 27.780552 | 81.925942 | 17.236008 | 7.873915 | 1.623758 | 6.247862 | 13.609598 | 18.910965 | 4.822454 | 16.753396 | 50.786096 | 17.358173 | 1.963652 | 4.572538 | 0.836153 | 13.587599 | 21.049449 | 35.105228 | 51.174381 | 73.906794 | 6.446348 | 4.854285 | 45.748197 | 52.935281 | 53.769274 | 14.136335 | 4.392162 | 10.154299 | 9.313996 | 8.550864 | 11.158701 | 5.219878 | 11.005356 | 1.612606 | 29.141104 | 42.366379 | 59.681979 | 76.522565 | 3527.744102 | 187.356402 | 664.004072 | 340.056387 | 387.027114 | 387.418302 | 430.792961 | 15722.738230 | 21.497935 | 16.907978 | 15.747380 | 18.337599 | 15.951463 | 5.586247 | 2.211892 | 0.93570 | 1.888588 | 14.795560 | 15.925492 | 16.433866 | 20.613246 | 18.665912 | 6.584413 | 2.602618 | 1.122699 | 2.281862 | 26.763353 | 6.102503 | 42.962971 | 10.740903 | 48.361978 | 50.746887 | 12.276181 | 76.095596 | 12.997495 | 2.398923 | 1.832421 | 0.454807 | 0.101895 | 0.239047 | 4.071333 | 3.253962 | 2.267587 | 18.299847 | 19.480380 | 23.723672 | 5.306324 | 60.042007 | 64.531600 | 73.852681 | 56.023833 | 69.801985 | 52.955299 | 64.110793 | 48.798568 | 70.102419 | 62.662768 | 6.636377 | 14.122762 | 12.595942 | 3.541054 | 12.403063 | 15.504989 | 0.419109 | 1.644709 | 10.544669 | 2.856286 | 11.376452 | 6.309227 | 4.012242 | 3.741877 | 3.156804 | 0.719176 | 6.411646 | 16.968442 | 4.280468 | 2.714805 | 4.369230 | 16.917882 | 6.860730 | 4.680638 | 3.286411 | 1.547415 | 8.047625 | 8.055653 | 6.477938 | 4.585262 | 7.008668 | 4.675408 | 3.187062 | 8.048537 | 69.567717 | 6.086299 | 0.497736 | 128.022534 | 8.770207 | 12.845963 | 28.725548 | 20.791337 | 6.544617 | 14.069824 | 7.366044 | 3.726156 | 22.092640 | 1.883704 | 17.130193 | 6.808756 | 0.596581 | 1.061554 | 0.145663 | 15.574278 | 31.269997 | 1.280216 | 30.583889 | 17.921792 | 33.375613 | 11.314132 | 0.719574 | 5.471565 | 0.865950 | 10.169947 | 0.190636 | 0.177546 | 4.850501 | 1.807257 | 0.775993 | 1.333239 | 0.167914 | 0.39625 | 0.726701 | 0.726533 | 0.078229 | 6.625005 | 57.032595 | 87.762860 | 5.985557 | 1.873265 | 3.454157 | 91.780667 | 60.37664 | 20.014474 | 6.861747 | 23.875498 | 2.589800 | 12.409791 | 22.694776 | 46.023687 | 62.414539 | 36.133537 | 2.744896 | 1.316344 | 51.869817 | 6.878464 | 29.802006 | 4.558336 | 0.070966 | 5.298736 | 82.630497 | 15.152863 | 71.944567 | 97.561565 | 94.393881 | 8.112837 | 2.331552 | 5.825871 | 5.981334 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 18.435144 | NaN | 46.973347 | 5.348939 | 12.856936 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 12.221074 | 14.540107 | 17.000000 | 14.35692 | 15.088435 | 15.673702 | 15.101013 | 15.415070 | 14.562430 | 14.859901 | 13.480100 | 13.252321 | 13.347521 | 14.032142 | 12.754589 | 12.283269 | 13.116019 | 14.262132 | 12.942051 | 12.266252 | 12.149945 | 11.364891 | 104.489351 | 9.602031 | 5.058242 | 7.933656 | NaN | 19.999790 | NaN | 17.313127 | NaN | NaN | NaN | 8.093739 | 13.347786 | 95778.176959 | 0.500618 | NaN | 1.910053 | NaN | NaN | NaN | NaN | NaN |
| std | NaN | NaN | 953.844476 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.806861 | 1.854960 | NaN | 2.742490 | 9.306899 | 0.470023 | 0.262078 | 1.669967 | 0.297344 | 0.821010 | 0.380916 | 0.276398 | 0.490414 | 0.427822 | 1.249891 | 0.728572 | 0.959573 | 0.077942 | 0.878639 | NaN | 5.065522 | 11.470554 | 15.097752 | 17.709065 | 4.391699 | 5.126618 | 4.155168 | NaN | NaN | NaN | 2.802759 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 5743.217266 | 1458.103434 | 2123.096242 | 47.430774 | 31.222078 | 40.037855 | 5.565579 | 5.768361 | 21.013875 | 16.690771 | 3.469319 | 7.069759 | 13.786061 | 0.679275 | 2.232166 | 2.533743 | 2.309205 | 1.003530 | 1.054121 | 1.169671 | 11.333534 | 1.292820 | 3.208650 | 3.365285 | 8.335618 | 8.249671 | 8.109103 | 7.261215 | 6.960006 | 6.882698 | 7.515298 | 8.232252 | 6.380545 | 5.827231 | 6.068227 | 7.787776 | 6.211045 | 4.316342 | 4.145509 | 6.003846 | 6.723718 | 5.120884 | 3.696610 | 5.384071 | 4.562136 | 5.642518 | 13.090318 | 7.44151 | 12.963903 | 11.769621 | 8.232499 | 14.538500 | 11.059218 | 6.382767 | 3.793017 | 12.967796 | 4.523434 | 4.887720 | 8.882360 | 50.041208 | 49.901819 | 24.974639 | 26.353147 | 5.365286 | 23.854442 | 22.645535 | 20.457755 | 5.906878 | 4.254839 | 3.969514 | 941.765892 | 947.384618 | 2.307938 | 2.244389 | 21.717078 | 20.900124 | 12.955210 | 9.960745 | 20.981653 | 13.03506 | 15.136752 | 16.239375 | 11.941462 | 14.106560 | 12.031207 | 5.297413 | 1.123896 | 4.683116 | 7.103567 | 9.355947 | 4.122604 | 6.862205 | 14.523902 | 12.299282 | 4.547730 | 10.073091 | 2.919611 | 26.623057 | 31.897623 | 36.644715 | 36.745060 | 29.596154 | 18.064895 | 7.545469 | 21.438911 | 10.734910 | 10.414782 | 2.559830 | 1.182950 | 12.790334 | 17.109430 | 14.403382 | 7.795426 | 7.459755 | 17.808023 | 3.021739 | 32.195145 | 34.930840 | 32.893874 | 24.275852 | 2863.904737 | 137.019184 | 116.363600 | 162.883283 | 173.614627 | 161.270738 | 171.643319 | 8563.646776 | 14.510598 | 7.959410 | 6.278437 | 7.438056 | 9.686003 | 5.835321 | 3.346289 | 1.92314 | 4.640740 | 12.341135 | 9.170850 | 7.640647 | 8.472725 | 10.644213 | 6.666176 | 3.907194 | 2.321726 | 5.531297 | 13.864884 | 6.215594 | 17.054347 | 9.967409 | 15.976535 | 16.044607 | 10.255140 | 13.289659 | 6.697763 | 5.590967 | 4.577517 | 2.197905 | 0.734757 | 0.695512 | 5.492788 | 3.687820 | 6.235675 | 19.057580 | 6.772797 | 6.630090 | 5.343132 | 17.401412 | 13.601579 | 14.643406 | 13.741904 | 14.983118 | 13.742309 | 16.390041 | 17.282413 | 30.768153 | 44.720850 | 9.249520 | 8.231474 | 7.138636 | 2.565171 | 5.540146 | 5.737145 | 0.995007 | 1.885284 | 6.027546 | 5.106797 | 5.859178 | 5.874676 | 3.223159 | 2.980044 | 5.570751 | 2.461053 | 4.122365 | 10.167102 | 3.201798 | 2.335400 | 3.097412 | 6.178759 | 4.660567 | 3.074098 | 3.227265 | 2.230989 | 4.496399 | 5.363320 | 4.354419 | 4.083389 | 4.267494 | 5.064888 | 4.161943 | 5.471748 | 12.300965 | 4.355084 | 1.035566 | 17.735576 | 8.278659 | 7.602447 | 10.258941 | 7.123331 | 3.397795 | 9.729814 | 7.057123 | 3.829339 | 7.745974 | 1.362423 | 6.372529 | 5.668213 | 3.169440 | 4.903344 | 1.066102 | 5.270476 | 10.475741 | 1.640392 | 14.494101 | 9.729102 | 17.052016 | 10.713996 | 2.294499 | 4.268972 | 1.360591 | 8.273017 | 0.707507 | 0.533090 | 3.321779 | 2.503596 | 2.139900 | 2.882133 | 0.866344 | 1.42636 | 0.977380 | 1.263606 | 0.388115 | 9.646192 | 21.780229 | 16.630083 | 12.043730 | 4.890662 | 4.503741 | 12.522388 | 18.80232 | 10.851776 | 3.995041 | 12.532295 | 5.991168 | 17.004746 | 23.922161 | 32.037812 | 31.747018 | 31.241492 | 7.690676 | 3.410360 | 35.645567 | 12.068323 | 27.973123 | 9.664122 | 0.493626 | 10.403123 | 28.465300 | 26.704108 | 35.581058 | 9.626052 | 10.739670 | 3.530980 | 0.866869 | 2.870344 | 3.252165 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 8.583794 | NaN | 22.970378 | 1.219785 | 4.544033 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 9.153015 | 14.548098 | 14.908052 | 10.06335 | 11.032013 | 12.153908 | 13.020388 | 12.356341 | 10.703185 | 10.848680 | 10.828587 | 9.453886 | 11.043516 | 10.948453 | 10.979879 | 11.787762 | 12.847063 | 10.161455 | 10.692959 | 9.179317 | 9.342705 | 8.708032 | 118.580367 | 8.554342 | 4.526651 | 8.784231 | NaN | 25.067746 | NaN | 13.956630 | NaN | NaN | NaN | 8.213242 | 10.769997 | 55284.596094 | 0.500002 | NaN | 1.072749 | NaN | NaN | NaN | NaN | NaN |
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99.000000 | 99.000000 | 99.000000 | 99.000000 | 9360.000000 | 651.000000 | 881.000000 | 1500.000000 | 1500.000000 | 1500.000000 | 1500.000000 | 174523.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 50.000000 | 61.00000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 50.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 71.000000 | 47.000000 | 25.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 90.000000 | 76.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 43.000000 | 55.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 65.000000 | 99.000000 | 99.000000 | 99.000000 | 64.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 67.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 170.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 37.000000 | 99.000000 | 99.000000 | 97.000000 | 99.000000 | 30.000000 | 72.000000 | 99.000000 | 97.000000 | 99.000000 | 78.000000 | 99.000000 | 99.000000 | 30.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 83.000000 | 99.000000 | 31.000000 | 92.000000 | 47.000000 | 14.000000 | 99.000000 | 55.000000 | 68.000000 | 99.000000 | 43.000000 | 52.00000 | 50.000000 | 27.000000 | 32.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.00000 | 99.000000 | 31.000000 | 52.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 90.000000 | 62.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 30.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 99.000000 | 21.000000 | 5.000000 | 99.000000 | 99.000000 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 61.000000 | NaN | 195.000000 | 19.000000 | 78.000000 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 50.000000 | 100.000000 | 50.000000 | 100.00000 | 250.000000 | 500.000000 | 1000.000000 | 500.000000 | 300.000000 | 300.000000 | 500.000000 | 200.000000 | 300.000000 | 500.000000 | 500.000000 | 1000.000000 | 970.000000 | 250.000000 | 300.000000 | 300.000000 | 200.000000 | 225.000000 | 9485.000000 | 237.000000 | 41.000000 | 1000.000000 | NaN | 5000.000000 | NaN | 1000.000000 | NaN | NaN | NaN | 1088.000000 | 1000.000000 | 191779.000000 | 1.000000 | NaN | 4.000000 | NaN | NaN | NaN | NaN | NaN |
# check incorrect values about promotions
for i in range(3, 25):
data['checker1'] = data['ADATE_' + str(i)] >= data['RDATE_' + str(i)]
data['checker2'] = data['RAMNT_' + str(i)].isna() & (data['RDATE_' + str(i)].isna() == False)
data['checker3'] = data['RDATE_' + str(i)].isna() & (data['RAMNT_' + str(i)].isna() == False)
for i in range(3, 25):
data['RFA_' + str(i)] = data['RFA_' + str(i)].apply(str.strip)
data['checker4'] = (data['RFA_' + str(i)] == '') & (data['ADATE_' + str(i)].isna() == False) | (data['RFA_' + str(i)] != '') & (data['ADATE_' + str(i)].isna() == True)
data['checker5'] = data['DOB'] >= data['FISTDATE']
print('RDATE before ADATE ', len(data.loc[data['checker1'] == True]))
print('Empty amount with not empty date ', len(data.loc[data['checker2'] == True]))
print('Empty date with not empty amount ',len(data.loc[data['checker3'] == True]))
print('Empty RFA with not empty ADATE and vice versa ',len(data.loc[data['checker4'] == True]))
print("DOB is later than one of dates ",len(data.loc[data['checker5'] == True]))
drop_lst=['checker' + str(i) for i in range(1, 6)]
data.drop(columns = drop_lst, inplace=True)
RDATE before ADATE 6999 Empty amount with not empty date 0 Empty date with not empty amount 0 Empty RFA with not empty ADATE and vice versa 0 DOB is later than one of dates 281
# RDATE's correction
modes = {'RDATE_' + str(i): data['RDATE_' + str(i)].mode() for i in range(3, 25)}
for i in range(3, 25):
data.loc[data['ADATE_' + str(i)] >= data['RDATE_' + str(i)], 'RDATE_' + str(i)] = modes['RDATE_' + str(i)].values[0]
# correction in ZIP codes (delete improper symbols)
data['ZIP'].replace(r'\-', '', regex=True, inplace=True)
# split MDMAUD into 4 columns, adding last one to the dataset, drop original because we already have MDMAUD_R, MDMAUD_F, MDMAUD_A
split_df = data['MDMAUD'].str.split('',expand=True)
data['MDMAUD_M'] = split_df[4]
data.drop(columns=['MDMAUD'], inplace=True)
exch_map = {'X': '0', 'M': '1'}
data['MDMAUD_M'] = data['MDMAUD_M'].map(exch_map)
# define exchenge dict for variables who can't be changed by ordinal encoder according metadata (including spaces replacing)
exch_dict = {
'NOEXCH': {'X': '0', ' ': '1', '0': '0', '1': '1'},
'GENDER': {'F': 'F', 'M': 'M', ' ': 'U', 'C': 'U', 'U': 'U', 'J': 'U', 'A': 'U'},
'SOLP3': {' ': '00', '00': '00', '12': '12', '01': '01', '02': '02'},
'SOLIH': {' ': '00', '12': '12', '00': '00', '02': '02', '01': '01', '04': '04', '06': '06', '03': '03'},
'HOMEOWNR':{' ': 'U', 'H': 'H','U':'U'}
}
for item in exch_dict.keys():
exch_map = exch_dict[item]
data[item] = data[item].map(exch_map)
# number of missing values per feature
data.isna().sum().loc[data.isna().sum() > 0].sort_values(ascending=False)
RDATE_5 95403
RAMNT_5 95403
RDATE_3 95170
RAMNT_3 95170
RDATE_4 95131
...
MSA 132
ADI 132
DMA 132
GEOCODE2 132
FISTDATE 2
Length: 92, dtype: int64
# rows with missed values in MSA, ADI, DMA & Geocode2
print('Rows with missed values in MSA, ADI, DMA & Geocode2 - ', len(data.loc[data['MSA'].isna() & data['ADI'].isna() & data['DMA'].isna() & data['GEOCODE2'].isna()].index.tolist()))
Rows with missed values in MSA, ADI, DMA & Geocode2 - 132
# delete rows from previous condition (4 NaN in a single row, record quality is low)
data.drop(np.where(data['MSA'].isna() & data['ADI'].isna() & data['DMA'].isna() & data['GEOCODE2'].isna())[0], inplace=True)
# drop 2 rows with FISTDATE == NaN becuse they are not donors
data.drop(data.loc[data['FISTDATE'].isna()].index, axis=0, inplace=True)
# exchange NaN with "0" because there is no missing values in HIT (Mail Order Response) and NaN in campaigns means the donor didn't response
fill_lst = ['NUMCHLD','MBCRAFT', 'MBGARDEN', 'MBBOOKS', 'MBCOLECT', 'MAGFAML', 'MAGFEM', 'MAGMALE', 'PUBGARDN', 'PUBCULIN', 'PUBHLTH',
'PUBDOITY', 'PUBNEWFN', 'PUBPHOTO', 'PUBOPP']+['ADATE_'+ str(i) for i in range(2, 25)] + ['RDATE_'+ str(i) for i in range(3, 25)]+ ['RAMNT_'+ str(i) for i in range(3, 25)]+ ['RFA_'+ str(i) for i in range(2, 25)]
for item in fill_lst:
data[item].fillna(0, inplace=True)
# donors who had the only one donation
data['NEXTDATE'].fillna(pd.Timestamp(0), inplace=True)
data['TIMELAG'].fillna(9999, inplace=True)
# calculating age, dropping DOB
data['AGE'] = 2017 - pd.to_datetime(data['DOB']).dt.year
data.drop(columns=['DOB'], inplace=True)
# NaN values
data.isna().sum().loc[data.isna().sum() > 0].sort_values(ascending=False)
WEALTH1 44632 WEALTH2 43766 AGE 23821 INCOME 21228 dtype: int64
# impute values into AGE column
data['AGE'].fillna(0, inplace=True)
mask = data['AGE'] < 15 # ages below 15 will be reset to 0
data.loc[mask, 'AGE'] = np.nan
target_lst = ['RAMNTALL', 'NGIFTALL', 'CARDGIFT', 'MINRAMNT', 'MAXRAMNT', 'LASTGIFT', 'AVGGIFT']
nan_var = ['WEALTH1','WEALTH2','AGE', 'INCOME']
iterative_data = data[nan_var + target_lst]
imp_mice = IterativeImputer(random_state=random_state)
imp_mice.fit(iterative_data)
X = imp_mice.transform(iterative_data)
data.loc[:,nan_var] = X[:,0:4]
data.loc[:,nan_var] = data.loc[:, nan_var].apply(np.rint)
#As part of feature engineering converting the promotion and dates (ADATE, RDATE) to months
dates = ['ADATE_'+ str(i) for i in range(2, 25)] + ['RDATE_'+ str(i) for i in range(3, 25)]+['FISTDATE', 'LASTDATE', 'MAXADATE', 'MINRDATE', 'NEXTDATE', 'MAXRDATE', 'ODATEDW']
for item in dates:
data['N_'+item] = (datetime.now().year-pd.to_datetime(data[item]).dt.year)*12+datetime.now().month-pd.to_datetime(data[item]).dt.month
data.drop(columns = dates, inplace=True)
data.info(verbose = False )
<class 'pandas.core.frame.DataFrame'> Int64Index: 95278 entries, 0 to 95411 Columns: 475 entries, OSOURCE to N_ODATEDW dtypes: float64(50), int64(353), object(72) memory usage: 346.0+ MB
main_data = data.copy().reset_index()
To visualise the distribution of the variables, we plot a histogram and a Q-Q plot in which if the variable is normally distributed, the values of the variable should fall in a 45 degree line when plotted against the theoretical quantiles.
def plots(df,feat,scaler):
plt.figure(figsize=(20, 5))
#1st->scaling
plt.subplot(1, 3, 1)
sns.kdeplot(scaler.fit_transform(df[[feat]]).flatten())
plt.title(str(scaler).split('(')[0]+': ' + feat)
#2nd->qqplot
qqplot(scaler.fit_transform(df[[feat]]).flatten(), line='q', ax=plt.subplot(1, 3, 2))
plt.title('QQ Plot: ' + feat)
plt.ylabel('Feature Quantiles')
#3rd->boxplot
plt.subplot(1, 3, 3)
sns.boxplot(y=df[feat])
plt.title('Boxplot: ' + feat)
metric_main=main_data.iloc[:,1:].select_dtypes(include='number')
non_metric_main=main_data.iloc[:,1:].select_dtypes(exclude=['number'])
for i in metric_main.columns[0:50]:
plots(metric_main, i, PowerTransformer(method='yeo-johnson'))
for i in metric_main.columns[0:50]:
plots(metric_main, i, QuantileTransformer(n_quantiles=500, output_distribution='normal', random_state=random_state))
We are going to use 2 common approaches to make data more Gaussian-like:
def data_normalization(df,index,random):
if (not os.path.exists('trans.pkl')) | recalculate:
main_df = df.set_index(index) if index!='' else df
metric_df = main_df.select_dtypes(include=['number'])
#Declare instances for qt & yj
yj = PowerTransformer(method='yeo-johnson')
qt = QuantileTransformer(n_quantiles=500, output_distribution='normal', random_state=random)
#Fit into qt & yeo-johnson
X_trans_yj = yj.fit_transform(metric_df)
X_trans_qt = qt.fit_transform(metric_df)
X_trans = np.concatenate((X_trans_yj, X_trans_qt), axis=1)
#Creating dataframe
merge_labels = list(map(lambda i:'yj_'+i, metric_df.columns.to_list()))+list(map(lambda i:'qt_'+ i, metric_df.columns.to_list()))
trans_df = pd.DataFrame(X_trans, columns=merge_labels, index=metric_df.index)
trans_df.to_pickle('trans.pkl')
else: trans_df = pd.read_pickle('trans.pkl')
#Get standarized dataframes
transyj_df = trans_df.loc[:,[i for i in trans_df.columns.to_list() if 'yj' in i]]
transqt_df = trans_df.loc[:,[i for i in trans_df.columns.to_list() if 'qt' in i]]
return transyj_df, transqt_df
def out_std(data, nstd=3.0, return_thresholds=False):
data_mean, data_std = data.mean(), data.std()
cut_off = data_std * nstd
lower, upper = data_mean - cut_off, data_mean + cut_off
if return_thresholds: return lower, upper
else: return data.apply(lambda i: np.any((i<lower)|(i>upper)),1)
def out_iqr(data, k=1.5, return_thresholds=False):
if (not os.path.exists('outlier_labels.pkl')) | recalculate:
#calculate the iq range
q25 , q75 = np.percentile(data, 25, axis=0), np.percentile(data, 75, axis=0)
iqr = q75 - q25
#calculate the outlier cutoff range
cut_off = iqr * k
lower, upper = q25 - cut_off, q75 + cut_off
if return_thresholds: return lower, upper
else: return data.apply(lambda i: np.any((i<lower)|(i>upper)),1) #return outliers
outlier_labels = pd.concat([out_iqr(transyj_df, 3.5), out_iqr(transqt_df, 3.5)], axis=1)
outlier_labels.columns = ['outyjiqr','outqtiqr']
outlier_labels.to_pickle('outlier_labels.pkl')
else:
outlier_labels = pd.read_pickle('outlier_labels.pkl')
transyj_df, transqt_df = data_normalization(main_data,'index',random_state)
fig,axes = plt.subplots(5,4, constrained_layout=True, figsize=(15,12))
for col,ax in zip(transyj_df.columns[0:20], axes.flatten()):
qqplot(transyj_df.loc[:,col], line='q', ax=ax)
ax.set_title(col)
for ax in fig.get_axes():
ax.label_outer()
plt.show()
#getting % of outliers by applying different computations: standard deviation & mean distance , iqr)
outlier_labels = pd.concat([out_std(transyj_df, 4), out_std(transqt_df, 4), out_iqr(transyj_df, 2.5), out_iqr(transqt_df, 2.5)], axis=1)
outlier_labels.columns = ['outyjstd','outqtstd','outyjiqr','outqtiqr']
print('% outliers after out_std & yeo-johnshon:',np.round(outlier_labels['outyjstd'].value_counts()[0]/len(outlier_labels)*100,2))
print('% outliers after out_std & quantile-transformation:',np.round(outlier_labels['outqtstd'].value_counts()[0]/len(outlier_labels)*100,2))
print('% outliers after iqr & yeo-johnshon:',np.round(outlier_labels['outyjiqr'].value_counts().values[0]/len(outlier_labels)*100,2))
print('% outliers after iqr & quantile-transformation:',np.round(outlier_labels['outqtiqr'].value_counts().values[0]/len(outlier_labels)*100,2))
% outliers after out_std & yeo-johnshon: 59.99 % outliers after out_std & quantile-transformation: 49.02 % outliers after iqr & yeo-johnshon: 99.94 % outliers after iqr & quantile-transformation: 100.0
After the data has been transformed by using some scaling & transformation techniques we conclude that are not appropiate for handling outliers hence we are going to apply different techniques as part of multivariate normal analysis
By using the functions out_std and out_iqr we obtain the potential outlier labels according to each transformation. The value 1 classifies an observation as a potential outlier as long as at least one variable has an abnormal value.
We define abnormal values has the ones outside the 2.5 x Interquantile Range (out_iqr) and the ones more than 4 Standard Deviations away from the mean (out_std). We defined this more unrestrictive criteria since the data already had high variation by nature.
def out_mahalanobis(data, random, contamination=0.03):
n=data.shape[0]
df=data.shape[1]
#Using ellipticenvelope to detect outliers in a transformed gaussian distributed dataset
ee_out=cov.EllipticEnvelope(contamination=contamination, support_fraction=0.95, random_state=random).fit(data)
#Computes the mahalanobis distances of given observations to the center
mahal=ee_out.mahalanobis(data)
#Obtain chi-square percentiles of each observations to the center
quantiles=chi2.ppf(q=np.fromfunction(lambda x:(x-0.5)/n,(n,)), df=df)
#Obtain set of predicted outliers those of which are distributed (1->inlier & -1->negative outlier)
labels=ee_out.predict(data)
return mahal, quantiles, labels
def remove_outliers(df,index,random):
#Apply data normalization
transyj_df, transqt_df = data_normalization(df,index,random)
#Call mahalanobis
if (not os.path.exists('lqt_lyj.pkl')) | recalculate:
mqt, qqt, lqt = out_mahalanobis(transqt_df, random)
myj, qyj, lyj = out_mahalanobis(transyj_df, random)
lqt_lyj = pd.DataFrame({'lqt': lqt, 'lyj': lyj}, index=df.set_index(index).index)
lqt_lyj.to_pickle('lqt_lyj.pkl')
else:
lqt_lyj = pd.read_pickle('lqt_lyj.pkl')
#Checking outliers precentage (1->inlier & -1->negative outlier)
inl = lqt_lyj.loc[(lqt_lyj['lqt'] == 1) & (lqt_lyj['lyj'] == 1)].sum()['lqt']
print('Outliers Percentage: {:4.2f}%'.format(100 - inl/len(lqt_lyj) * 100))
#Creating mask for outliers' drop
lqt_lyj.loc[(lqt_lyj['lqt'] == 1) & (lqt_lyj['lyj'] == 1), 'mask'] = True
lqt_lyj.fillna(False, inplace=True)
lqt_lyj.drop(columns=['lqt', 'lyj'], inplace=True)
#Update dataframe marking the outliers for remotion
main_df = df.set_index(index).merge(lqt_lyj, left_index=True, right_index=True)
clean_df = main_df.loc[main_df['mask'] == True]
clean_df.drop(columns=['mask'], inplace=True)
return clean_df
def apply_multivariate_transfomer(yt_df,qt_df,random):
myj, qyj, lyj = out_mahalanobis(yt_df,random)
mqt, qqt, lqt = out_mahalanobis(qt_df,random)
lqt_lyj = pd.DataFrame({'lqt': lqt, 'lyj': lyj})
return [[np.sort(myj), qyj, 'Yeo-Johnson'], [np.sort(mqt), qqt, 'Quantile Transformation']]
def plot_outlier_fitting(values):
fig, axes = plt.subplots(1, 2, constrained_layout=True, figsize=(15,6))
fig.suptitle('Chi-Square Plot', fontsize=25)
for ax,v in zip(axes.flatten(), values):
ax.scatter(v[1], v[0], s=25)
ax.plot(v[1], v[1], '-r', label='Multivariate Normality')
ax.legend(loc='upper left')
ax.set_title(v[2])
ax.set_xlabel('Chi-Square Quantiles')
ax.set_ylabel('Mahalanobis')
plt.show()
main_values_transf=apply_multivariate_transfomer(transyj_df,transqt_df,random_state)
plot_outlier_fitting(main_values_transf)
cleaned_data=remove_outliers(main_data,'index',random_state)
Outliers Percentage: 4.84%
transyj_out_df, transqt_out_df = data_normalization(cleaned_data,'',random_state)
main_out_transf=apply_multivariate_transfomer(transyj_out_df,transqt_out_df,random_state)
plot_outlier_fitting(main_out_transf)
def get_cat_outliers(df,dtypes,coeff):
dict={}
#list of categorical variables
for i in df.select_dtypes(include=dtypes).columns:
aItem=[]
for j in range(len(df[i].value_counts())):
#define a threshold to get those elements that don't match the minimum number of ocurrances
#the comparision is against the maximum number of ocurrances per column
if np.round(df[i].value_counts()[j]/df[i].value_counts().max(),2)*100<coeff:
aItem.append(df[i].value_counts().index[j])
#append to the dictionary
if len(aItem)>0: dict.update({i:aItem})
return dict #return the list of categorical variables with the elements that dont fullfilled the threshold
#define 1% as minimum outlier coefficient & get the list of elements
cat_outliers=get_cat_outliers(cleaned_data,['object'],1)
#check the results
for i in cat_outliers.keys():
nOut=len(cleaned_data[cleaned_data[i].isin(cat_outliers[i])])
print('Categorical Variable: {}, Records: {}, Percentage: {}%'.format(i,nOut,np.round(nOut/len(cleaned_data[i])*100,2)))
Categorical Variable: OSOURCE, Records: 3469, Percentage: 3.83% Categorical Variable: STATE, Records: 423, Percentage: 0.47% Categorical Variable: PVASTATE, Records: 5, Percentage: 0.01% Categorical Variable: NOEXCH, Records: 277, Percentage: 0.31% Categorical Variable: RECPGVG, Records: 109, Percentage: 0.12% Categorical Variable: CHILD03, Records: 264, Percentage: 0.29% Categorical Variable: CHILD07, Records: 483, Percentage: 0.53% Categorical Variable: CHILD12, Records: 137, Percentage: 0.15% Categorical Variable: CHILD18, Records: 253, Percentage: 0.28% Categorical Variable: SOLP3, Records: 88, Percentage: 0.1% Categorical Variable: SOLIH, Records: 196, Percentage: 0.22% Categorical Variable: MAJOR, Records: 282, Percentage: 0.31% Categorical Variable: RFA_3, Records: 953, Percentage: 1.05% Categorical Variable: RFA_4, Records: 617, Percentage: 0.68% Categorical Variable: RFA_5, Records: 425, Percentage: 0.47% Categorical Variable: RFA_6, Records: 652, Percentage: 0.72% Categorical Variable: RFA_7, Records: 455, Percentage: 0.5% Categorical Variable: RFA_8, Records: 495, Percentage: 0.55% Categorical Variable: RFA_9, Records: 563, Percentage: 0.62% Categorical Variable: RFA_10, Records: 636, Percentage: 0.7% Categorical Variable: RFA_11, Records: 411, Percentage: 0.45% Categorical Variable: RFA_12, Records: 453, Percentage: 0.5% Categorical Variable: RFA_13, Records: 1044, Percentage: 1.15% Categorical Variable: RFA_14, Records: 727, Percentage: 0.8% Categorical Variable: RFA_15, Records: 1051, Percentage: 1.16% Categorical Variable: RFA_16, Records: 1245, Percentage: 1.37% Categorical Variable: RFA_17, Records: 2096, Percentage: 2.31% Categorical Variable: RFA_18, Records: 1495, Percentage: 1.65% Categorical Variable: RFA_19, Records: 1346, Percentage: 1.48% Categorical Variable: RFA_20, Records: 2891, Percentage: 3.19% Categorical Variable: RFA_21, Records: 2499, Percentage: 2.76% Categorical Variable: RFA_22, Records: 1981, Percentage: 2.19% Categorical Variable: RFA_23, Records: 1915, Percentage: 2.11% Categorical Variable: RFA_24, Records: 2305, Percentage: 2.54% Categorical Variable: MDMAUD_R, Records: 282, Percentage: 0.31% Categorical Variable: MDMAUD_F, Records: 282, Percentage: 0.31% Categorical Variable: MDMAUD_A, Records: 282, Percentage: 0.31% Categorical Variable: MDMAUD_M, Records: 282, Percentage: 0.31%
#Backup the dataframe & remove the elements
#cleaned_df=cleaned_data.copy()
#for i in list(cat_outliers.keys()):
# cleaned_df.drop(index=list(cleaned_df[cleaned_df[i].isin(cat_outliers[i])].loc[:,i].index),axis=0,inplace=True)
#print('Percentage of categorical outliers removed:',np.round((len(cleaned_data)-len(cleaned_df))/len(cleaned_data),2)*100)
def apply_umap(df,normalize=True):
metric=df.select_dtypes(include='number')
#apply data scaling transformation
if normalize:
for i in metric:
metric.loc[:,i]=PowerTransformer(method='yeo-johnson').fit_transform(np.array(metric[i]).reshape(-1,1))
#applying get_dummies for categorical
non_metric=pd.get_dummies(df.select_dtypes(include='object'))
non_metric_weight=len(df.select_dtypes(include='object').columns)/df.shape[1]
#embedding numerical & categorical
fit1=umap.UMAP(metric='l2').fit(metric)
fit2=umap.UMAP(metric='dice').fit(non_metric)
#sugmenting the numerical embedding with categorical
intersection = umap.umap_.general_simplicial_set_intersection(fit1.graph_, fit2.graph_, weight=non_metric_weight)
intersection = umap.umap_.reset_local_connectivity(intersection)
#perform a fuzzy simplicial set embedding, using a specified initialization method and then minimizing the fuzzy set cross entropy
embedding = umap.umap_.simplicial_set_embedding(fit1._raw_data, intersection, fit1.n_components,
fit1._initial_alpha, fit1._a, fit1._b,
fit1.repulsion_strength, fit1.negative_sample_rate,
200, 'random', np.random, fit1.metric,
fit1._metric_kwds, False)
return embedding
embedding=apply_umap(cleaned_data,False)
plt.figure(figsize=(20, 10))
plt.scatter(*embedding.T, s=2, cmap='Spectral', alpha=1.0)
plt.show()
embedding=apply_umap(cleaned_data)
plt.figure(figsize=(20, 10))
plt.scatter(*embedding.T, s=2, cmap='Spectral', alpha=1.0)
plt.show()
group=pd.read_excel(os.path.join(os.getcwd(),'Data/group.xlsx'))
aColumns=['FISTDATE','NEXTDATE','MINRDATE','MAXADATE','ODATEDW','MAXRDATE','LASTDATE']
for i in aColumns:
group['Var']=group['Var'].str.replace(i, 'N_'+i, regex=False)
group=group.groupby('Group', as_index=False).agg({'Var': ','.join})
metric_cleaned=cleaned_data.select_dtypes(include='number').columns.tolist()
non_metric_cleaned=cleaned_data.select_dtypes(exclude='number').columns.tolist()
data_ss=pd.DataFrame(StandardScaler().fit_transform(cleaned_data[metric_cleaned]),columns=metric_cleaned).set_index(cleaned_data.index)
data_ss=pd.concat([data_ss,cleaned_data.loc[:,non_metric_cleaned]],axis=1)
data_ss.head()
| TCODE | NUMCHLD | INCOME | WEALTH1 | HIT | MBCRAFT | MBGARDEN | MBBOOKS | MBCOLECT | MAGFAML | MAGFEM | MAGMALE | PUBGARDN | PUBCULIN | PUBHLTH | PUBDOITY | PUBNEWFN | PUBPHOTO | PUBOPP | MALEMILI | MALEVET | VIETVETS | WWIIVETS | LOCALGOV | STATEGOV | FEDGOV | WEALTH2 | POP901 | POP902 | POP903 | POP90C1 | POP90C2 | POP90C3 | POP90C4 | POP90C5 | ETH1 | ETH2 | ETH3 | ETH4 | ETH5 | ETH6 | ETH7 | ETH8 | ETH9 | ETH10 | ETH11 | ETH12 | ETH13 | ETH14 | ETH15 | ETH16 | AGE901 | AGE902 | AGE903 | AGE904 | AGE905 | AGE906 | AGE907 | CHIL1 | CHIL2 | CHIL3 | AGEC1 | AGEC2 | AGEC3 | AGEC4 | AGEC5 | AGEC6 | AGEC7 | CHILC1 | CHILC2 | CHILC3 | CHILC4 | CHILC5 | HHAGE1 | HHAGE2 | HHAGE3 | HHN1 | HHN2 | HHN3 | HHN4 | HHN5 | HHN6 | MARR1 | MARR2 | MARR3 | MARR4 | HHP1 | HHP2 | DW1 | DW2 | DW3 | DW4 | DW5 | DW6 | DW7 | DW8 | DW9 | HV1 | HV2 | HV3 | HV4 | HU1 | HU2 | HU3 | HU4 | HU5 | HHD1 | HHD2 | HHD3 | HHD4 | HHD5 | HHD6 | HHD7 | HHD8 | HHD9 | HHD10 | HHD11 | HHD12 | ETHC1 | ETHC2 | ETHC3 | ETHC4 | ETHC5 | ETHC6 | HVP1 | HVP2 | HVP3 | HVP4 | HVP5 | HVP6 | HUR1 | HUR2 | RHP1 | RHP2 | RHP3 | RHP4 | HUPA1 | HUPA2 | HUPA3 | HUPA4 | HUPA5 | HUPA6 | HUPA7 | RP1 | RP2 | RP3 | RP4 | MSA | ADI | DMA | IC1 | IC2 | IC3 | IC4 | IC5 | IC6 | IC7 | IC8 | IC9 | IC10 | IC11 | IC12 | IC13 | IC14 | IC15 | IC16 | IC17 | IC18 | IC19 | IC20 | IC21 | IC22 | IC23 | HHAS1 | HHAS2 | HHAS3 | HHAS4 | MC1 | MC2 | MC3 | TPE1 | TPE2 | TPE3 | TPE4 | TPE5 | TPE6 | TPE7 | TPE8 | TPE9 | PEC1 | PEC2 | TPE10 | TPE11 | TPE12 | TPE13 | LFC1 | LFC2 | LFC3 | LFC4 | LFC5 | LFC6 | LFC7 | LFC8 | LFC9 | LFC10 | OCC1 | OCC2 | OCC3 | OCC4 | OCC5 | OCC6 | OCC7 | OCC8 | OCC9 | OCC10 | OCC11 | OCC12 | OCC13 | EIC1 | EIC2 | EIC3 | EIC4 | EIC5 | EIC6 | EIC7 | EIC8 | EIC9 | EIC10 | EIC11 | EIC12 | EIC13 | EIC14 | EIC15 | EIC16 | OEDC1 | OEDC2 | OEDC3 | OEDC4 | OEDC5 | OEDC6 | OEDC7 | EC1 | EC2 | EC3 | EC4 | EC5 | EC6 | EC7 | EC8 | SEC1 | SEC2 | SEC3 | SEC4 | SEC5 | AFC1 | AFC2 | AFC3 | AFC4 | AFC5 | AFC6 | VC1 | VC2 | VC3 | VC4 | ANC1 | ANC2 | ANC3 | ANC4 | ANC5 | ANC6 | ANC7 | ANC8 | ANC9 | ANC10 | ANC11 | ANC12 | ANC13 | ANC14 | ANC15 | POBC1 | POBC2 | LSC1 | LSC2 | LSC3 | LSC4 | VOC1 | VOC2 | VOC3 | HC1 | HC2 | HC3 | HC4 | HC5 | HC6 | HC7 | HC8 | HC9 | HC10 | HC11 | HC12 | HC13 | HC14 | HC15 | HC16 | HC17 | HC18 | HC19 | HC20 | HC21 | MHUC1 | MHUC2 | AC1 | AC2 | CARDPROM | NUMPROM | CARDPM12 | NUMPRM12 | RAMNT_3 | RAMNT_4 | RAMNT_5 | RAMNT_6 | RAMNT_7 | RAMNT_8 | RAMNT_9 | RAMNT_10 | RAMNT_11 | RAMNT_12 | RAMNT_13 | RAMNT_14 | RAMNT_15 | RAMNT_16 | RAMNT_17 | RAMNT_18 | RAMNT_19 | RAMNT_20 | RAMNT_21 | RAMNT_22 | RAMNT_23 | RAMNT_24 | RAMNTALL | NGIFTALL | CARDGIFT | MINRAMNT | MAXRAMNT | LASTGIFT | TIMELAG | AVGGIFT | CONTROLN | HPHONE_D | RFA_2F | AGE | N_ADATE_2 | N_ADATE_3 | N_ADATE_4 | N_ADATE_5 | N_ADATE_6 | N_ADATE_7 | N_ADATE_8 | N_ADATE_9 | N_ADATE_10 | N_ADATE_11 | N_ADATE_12 | N_ADATE_13 | N_ADATE_14 | N_ADATE_15 | N_ADATE_16 | N_ADATE_17 | N_ADATE_18 | N_ADATE_19 | N_ADATE_20 | N_ADATE_21 | N_ADATE_22 | N_ADATE_23 | N_ADATE_24 | N_RDATE_3 | N_RDATE_4 | N_RDATE_5 | N_RDATE_6 | N_RDATE_7 | N_RDATE_8 | N_RDATE_9 | N_RDATE_10 | N_RDATE_11 | N_RDATE_12 | N_RDATE_13 | N_RDATE_14 | N_RDATE_15 | N_RDATE_16 | N_RDATE_17 | N_RDATE_18 | N_RDATE_19 | N_RDATE_20 | N_RDATE_21 | N_RDATE_22 | N_RDATE_23 | N_RDATE_24 | N_FISTDATE | N_LASTDATE | N_MAXADATE | N_MINRDATE | N_NEXTDATE | N_MAXRDATE | N_ODATEDW | OSOURCE | STATE | ZIP | MAILCODE | PVASTATE | NOEXCH | RECINHSE | RECP3 | RECPGVG | RECSWEEP | DOMAIN | HOMEOWNR | CHILD03 | CHILD07 | CHILD12 | CHILD18 | GENDER | DATASRCE | SOLP3 | SOLIH | MAJOR | GEOCODE | COLLECT1 | VETERANS | BIBLE | CATLG | HOMEE | PETS | CDPLAY | STEREO | PCOWNERS | PHOTO | CRAFTS | FISHER | GARDENIN | BOATS | WALKER | KIDSTUFF | CARDS | PLATES | LIFESRC | PEPSTRFL | RFA_2 | RFA_3 | RFA_4 | RFA_5 | RFA_6 | RFA_7 | RFA_8 | RFA_9 | RFA_10 | RFA_11 | RFA_12 | RFA_13 | RFA_14 | RFA_15 | RFA_16 | RFA_17 | RFA_18 | RFA_19 | RFA_20 | RFA_21 | RFA_22 | RFA_23 | RFA_24 | RFA_2R | RFA_2A | MDMAUD_R | MDMAUD_F | MDMAUD_A | GEOCODE2 | MDMAUD_M | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| index | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 0 | -0.056484 | -0.339022 | 0.063326 | -0.067802 | -0.359111 | -0.210819 | -0.148904 | -0.401004 | -0.141417 | -0.339122 | -0.215411 | -0.157479 | -0.190095 | -0.220597 | -0.351784 | -0.2129 | -0.252319 | -0.050476 | -0.17738 | -0.222578 | 0.764555 | 0.273976 | -0.843689 | 0.723900 | -0.510961 | -0.521341 | -0.039547 | -0.400929 | -0.418980 | -0.424284 | -1.227379 | 0.680791 | 0.955419 | -0.257079 | 0.383747 | 0.337501 | -0.385888 | -0.224102 | -0.411650 | 0.252353 | -0.319811 | -0.178221 | -0.246320 | -0.243474 | -0.248958 | -0.200139 | -0.058664 | 0.511294 | -0.23121 | -0.102556 | -0.451870 | 0.612066 | 0.802545 | 0.787717 | 0.641032 | 0.837220 | 0.969850 | 0.026052 | -1.177562 | 0.621162 | 1.257676 | -0.213290 | -1.125645 | -0.485091 | 0.687266 | 0.272974 | 0.098169 | 1.252122 | -0.927598 | -1.641501 | 0.465463 | 1.282771 | 0.734759 | 0.137703 | 0.121957 | 0.081820 | -0.414011 | -0.085704 | 0.426980 | 0.202780 | 0.232371 | 0.019686 | 0.210179 | -0.869584 | 1.039638 | -0.472630 | 0.244572 | 0.317156 | 1.089906 | 1.107528 | -0.168975 | -0.736529 | -0.736861 | -0.645693 | 1.337268 | 1.794621 | -0.190222 | -0.623722 | -0.530412 | -0.533467 | -0.841562 | 0.763339 | -0.755580 | 0.469937 | -0.520164 | -0.320463 | 0.160755 | 0.566972 | 0.703681 | 0.347877 | 0.110960 | -0.066387 | -0.380719 | 0.328094 | -0.289357 | -0.687354 | -0.424148 | -0.471556 | 0.004574 | -0.075568 | 0.722313 | -0.433888 | -0.452631 | -0.293593 | -0.436465 | -0.441974 | -0.605256 | -0.662689 | -0.929058 | -0.357903 | -0.540601 | 0.711199 | 0.469802 | 0.705414 | 0.338784 | -0.357274 | -0.643387 | -0.550519 | -0.604606 | 0.385988 | -0.573573 | -0.627901 | -0.552639 | -0.843058 | -1.071013 | -1.305531 | -0.158649 | -1.225051 | -0.077854 | 0.152047 | -0.215381 | -0.412202 | -0.252248 | -0.321506 | -0.335833 | -0.593365 | 0.786031 | 1.179889 | 0.625643 | -0.113771 | -0.799118 | -0.670050 | -0.498772 | -0.192632 | -0.894584 | 1.020116 | 1.019073 | 0.640333 | -0.173040 | -0.698952 | -0.675088 | -0.502388 | -0.048126 | 0.112064 | -0.349608 | 0.486998 | -1.005144 | -0.143075 | 0.187062 | -0.936860 | 0.937989 | -0.781837 | -0.435132 | -0.408812 | -0.208058 | -0.140325 | -0.35014 | -0.830457 | 0.221224 | -0.204598 | -0.286803 | -0.875025 | -1.209488 | -0.633701 | -0.902419 | -0.726379 | -0.790413 | -0.501819 | -0.465944 | -0.723296 | -0.185318 | 0.222852 | 0.938588 | -1.435782 | -0.747978 | -0.635447 | -1.384964 | 1.830747 | 0.117900 | -1.185488 | -0.444443 | 0.775792 | -0.262864 | 0.024844 | 0.614041 | 2.168132 | 0.308171 | 0.080281 | -0.033042 | -0.295718 | -0.878285 | 2.372038 | -1.073211 | -1.199181 | 0.890419 | -0.667248 | -0.186145 | 0.109148 | -1.080815 | 1.179881 | 0.220283 | -0.793328 | -1.312817 | -0.401284 | 0.705981 | -0.542357 | -0.550613 | -0.203340 | 0.705243 | -1.008563 | -0.528925 | -0.472421 | 0.878853 | -0.386639 | 1.007372 | 0.026436 | 0.423259 | -1.045121 | -0.624503 | 0.383717 | -0.312505 | 0.821431 | 0.271355 | -0.568357 | -0.237232 | -0.255253 | -0.175025 | 0.473689 | 0.765910 | -0.800469 | 0.221642 | 0.519058 | -0.932566 | 0.474987 | 0.122485 | -0.350151 | -0.641171 | 1.553803 | -0.280742 | -0.332656 | 0.041842 | -0.320802 | -0.366841 | -0.467122 | -0.195031 | -0.279237 | -0.763291 | 1.021941 | -0.203149 | -0.375935 | 0.772384 | 0.004289 | 0.163361 | -0.384928 | 0.127814 | 0.337490 | 0.891090 | -0.121232 | 1.545948 | 0.568460 | 0.422711 | 0.095558 | -0.370246 | -0.478273 | -0.275877 | 0.307208 | -0.364774 | -0.38569 | 1.066676 | -0.576280 | -0.708454 | -0.476034 | -0.144517 | -0.514837 | -1.750102 | 1.848302 | -0.892557 | 0.143742 | 0.453107 | -0.639534 | -0.420779 | 1.493513 | 0.322203 | 1.009324 | 1.189622 | 0.549621 | 0.256274 | -0.035562 | -0.03654 | 0.0 | -0.004697 | -0.253723 | -0.404434 | -0.333796 | 1.300381 | -0.334003 | -0.460123 | -0.28932 | 0.908426 | 2.132507 | 0.812686 | 1.889509 | -0.342138 | -0.309369 | -0.241026 | -0.251325 | -0.401299 | 2.330457 | 1.181792 | 1.148973 | 2.614626 | 2.055903 | -0.341080 | -0.320077 | -0.538167 | -0.346365 | -0.529109 | -0.002089 | -1.002363 | 2.006185 | 0.076991 | 0.0 | -0.125011 | -0.134606 | -0.732418 | -0.195915 | -0.309852 | -0.196628 | -0.367887 | -0.715766 | -0.344450 | -0.319305 | -0.853900 | -0.492918 | -1.487472 | -0.524857 | -0.634621 | -0.541803 | -0.591157 | -1.048237 | -0.759348 | -0.610267 | -1.203835 | -0.795329 | 0.041781 | 0.051518 | 0.0 | 0.004697 | 0.316734 | 0.534469 | 0.456322 | -2.868775 | 0.423778 | 0.599951 | 0.377492 | -1.777113 | -3.563078 | -1.611042 | -3.059769 | 0.501695 | 0.44144 | 0.297813 | 0.329249 | 0.521229 | -3.440912 | -2.126740 | 0.612021 | -0.107034 | 0.0 | 0.116188 | -0.203579 | 0.463110 | 0.708650 | GRI | IL | 61081 | 0 | T2 | U | F | 00 | 00 | X | L4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | L | E | X | X | X | C | 0 | ||||||||||||||||||||||||||||||||
| 1 | -0.055449 | 1.344798 | 1.255951 | 1.581978 | 1.368227 | -0.210819 | -0.148904 | 1.994135 | 4.853188 | 1.346949 | 3.598216 | -0.157479 | -0.190095 | -0.220597 | 1.849663 | -0.2129 | 4.241632 | -0.050476 | -0.17738 | -0.222578 | -1.387297 | 1.687688 | -1.250826 | -0.205055 | -0.510961 | -0.521341 | 1.589457 | 0.056085 | 0.042738 | -0.112359 | 0.857892 | -0.438579 | -0.660485 | 0.358783 | -0.208358 | -0.870392 | -0.446136 | -0.224102 | 3.951649 | -0.109529 | 5.620208 | 0.705663 | 2.158274 | 1.476575 | 13.587410 | -0.200139 | -0.058664 | -0.280240 | -0.23121 | 0.210158 | 0.736505 | -0.042118 | -0.112977 | -0.269820 | -0.576224 | -0.421976 | -0.452609 | 1.020966 | -0.906860 | 1.357364 | 0.002455 | 0.172487 | -1.125645 | 2.070699 | 2.159728 | -0.483579 | -1.161970 | -0.914428 | -1.148503 | -0.075319 | 0.909397 | 0.527969 | -0.016030 | -1.019553 | -1.211305 | -1.422862 | -1.685445 | -1.636875 | 2.305686 | 2.739557 | 2.003524 | 1.375084 | 0.866471 | -1.571933 | -0.965546 | 0.144947 | 2.720083 | 2.095607 | 1.172748 | 1.264283 | -0.545252 | -0.823188 | -0.736861 | -0.645693 | -0.361480 | -0.314121 | -0.190222 | 4.690300 | 4.320203 | 3.399904 | 2.739083 | 1.246899 | -1.256158 | 0.550987 | -0.622140 | -0.224762 | 1.857523 | 1.554639 | 1.862987 | 2.366836 | 0.982582 | -1.098325 | -0.766439 | -0.598649 | -0.725716 | -1.297034 | -1.666313 | -0.735082 | 0.155821 | -0.504829 | -1.090262 | -0.433888 | -0.452631 | -0.293593 | 3.126403 | 2.408794 | 1.716545 | 1.275001 | 0.849899 | 4.852715 | -0.688177 | 1.761072 | 2.223415 | 1.913316 | 2.812726 | 0.528263 | -0.803009 | -0.550519 | -0.604606 | -0.988651 | -0.709884 | -0.627901 | -0.552639 | 1.922401 | 1.391349 | 0.949790 | 0.717853 | 0.337828 | -1.272832 | 1.190439 | 4.674425 | 4.158349 | 4.026272 | 3.595169 | 2.424953 | -1.372866 | -1.407899 | -2.268238 | -1.864825 | -0.113771 | 1.453033 | 3.264644 | 4.863777 | 6.870120 | -1.060779 | -1.226764 | -1.962232 | -1.918707 | -0.363987 | 1.121146 | 2.957630 | 4.007486 | 5.507478 | -1.585098 | -0.680710 | 1.387632 | -0.796911 | 0.505061 | -0.458332 | -0.315187 | 0.284867 | 0.137548 | -0.435132 | -0.408812 | -0.208058 | -0.140325 | -0.35014 | -0.830457 | 0.799390 | -0.364830 | -0.863959 | 0.725679 | 1.260450 | 1.260461 | 0.628067 | 0.396995 | 0.645639 | 0.118820 | 0.775148 | 0.279223 | -0.051607 | 0.466519 | 0.938588 | 0.796750 | -0.747978 | 0.977539 | 1.644343 | 0.186351 | 1.630964 | -0.457919 | 1.689665 | -0.362055 | -0.782914 | -0.570236 | -1.318591 | -0.924422 | -1.302021 | -0.268068 | -0.396796 | -0.295718 | -0.119739 | -0.409249 | -1.073211 | -0.323729 | 1.231448 | 0.181598 | 0.935558 | -0.234246 | -0.089005 | 1.179881 | 0.453094 | -0.204746 | 1.098094 | -0.904374 | -0.256148 | -0.542357 | -0.550613 | 1.490483 | -0.069202 | -0.256000 | 1.594600 | 1.872814 | -0.464955 | -1.054361 | -1.674815 | 0.026436 | 0.124679 | 1.660326 | 1.835035 | 3.039195 | 0.244905 | 1.571172 | 1.094750 | 0.699592 | -0.237232 | -0.255253 | -0.175025 | -1.507251 | -1.633262 | -0.800469 | 1.708560 | -0.846702 | -1.360076 | -1.116572 | -0.311938 | -0.824017 | -0.641171 | -0.867754 | 1.206064 | 1.590768 | -0.873059 | 0.488057 | 0.109322 | -0.111169 | -0.195031 | 1.893021 | -0.763291 | -0.575576 | -0.203149 | 3.675802 | -0.873355 | -2.342765 | 0.080499 | 5.122306 | 2.821731 | 0.604384 | 1.725509 | 3.083298 | -0.480434 | -1.120901 | -0.098964 | 0.814259 | 1.406610 | 1.601300 | 1.160301 | -1.174051 | -0.364774 | -0.38569 | 1.235585 | -0.576280 | -0.925629 | -0.476034 | -0.144517 | -0.514837 | 0.578396 | -0.573274 | 0.766683 | 0.143742 | 0.453107 | 3.440463 | 1.983118 | 0.043207 | -0.320933 | -0.746145 | -0.649703 | 0.549621 | 0.031436 | -0.035562 | -0.03654 | 0.0 | -0.004697 | -0.253723 | -0.404434 | 2.806008 | -0.268587 | -0.334003 | -0.460123 | -0.28932 | -0.439709 | -0.215969 | 0.928487 | -0.245018 | -0.342138 | -0.309369 | -0.241026 | -0.251325 | -0.401299 | -0.231453 | -0.361942 | -0.483569 | -0.771030 | -0.896587 | 0.223657 | 0.190558 | 0.541025 | -0.341820 | 0.202688 | 0.961921 | -1.002363 | 0.111907 | -0.974170 | 0.0 | -0.125011 | -0.134606 | -0.732418 | -0.195915 | -0.309852 | -0.196628 | -0.367887 | -0.715766 | -0.344450 | -0.325565 | 1.171237 | 2.028812 | 0.672282 | -0.524857 | 1.576554 | 1.851932 | -0.591157 | -1.048237 | -0.759348 | -0.610267 | 0.830703 | -0.795329 | 0.041781 | 0.051518 | 0.0 | 0.004697 | 0.316734 | 0.534469 | -2.190952 | 0.348845 | 0.423778 | 0.599951 | 0.377492 | 0.563022 | 0.280293 | -1.606939 | 0.326546 | 0.501695 | 0.44144 | 0.297813 | 0.329249 | 0.521229 | 0.290397 | 0.469795 | -0.639778 | -0.107034 | 0.0 | -0.323100 | -0.587980 | -0.628517 | -0.748680 | BOA | CA | 91326 | 0 | S1 | H | M | M | 3 | 00 | 00 | 02 | L2G | A2G | A2G | A2G | A2G | A1E | A1E | A1E | A1E | A1E | A1E | L1E | N1E | N1E | N1E | N1E | F1E | L | G | X | X | X | A | 0 | ||||||||||||||||||||||||||||||||||||
| 2 | -0.055449 | -0.339022 | -0.532986 | -1.717583 | -0.143194 | -0.210819 | -0.148904 | 0.397376 | -0.141417 | -0.339122 | -0.215411 | -0.157479 | -0.190095 | -0.220597 | 0.748939 | -0.2129 | -0.252319 | -0.050476 | -0.17738 | -0.222578 | -0.938995 | -0.062622 | 0.028746 | -0.205055 | 0.681567 | -0.521341 | -1.668552 | 0.647638 | 0.794053 | 0.670265 | -1.227379 | -0.374615 | 1.775800 | 0.153496 | -0.010989 | 0.530764 | -0.325639 | -0.224102 | -0.411650 | -0.399034 | -0.319811 | -0.178221 | -0.246320 | -0.243474 | -0.248958 | -0.200139 | -0.058664 | -0.280240 | -0.23121 | -0.102556 | -0.451870 | 0.088719 | 0.148601 | 0.126756 | 0.184561 | 0.050222 | 0.179595 | -0.258209 | -0.636159 | 0.253061 | 0.839269 | 0.172487 | -0.312114 | -0.314705 | 0.441856 | 0.272974 | -0.081851 | 0.085518 | -0.264883 | -0.701792 | -0.422407 | 0.527969 | 0.985022 | 0.055041 | 0.121957 | 0.081820 | -0.141561 | 0.172825 | 0.065691 | -0.360949 | -0.733712 | -0.522473 | 0.374252 | -0.401351 | 0.371244 | -0.472630 | -0.067467 | -0.148629 | -0.069879 | 0.088619 | -0.357114 | -0.563210 | -0.507681 | -0.492640 | 0.366555 | 0.589625 | -0.190222 | -0.604549 | -0.624609 | -0.970508 | -1.289143 | 0.376491 | -0.355118 | 0.226786 | -0.214236 | 0.205896 | -0.000842 | 0.284781 | 0.381652 | 0.172315 | 0.269437 | -0.254012 | -0.187859 | 0.328094 | -0.289357 | -0.382514 | -0.198300 | -0.471556 | 0.004574 | 0.639867 | 0.087912 | -0.433888 | -0.352315 | -0.293593 | -0.511473 | -0.629937 | -0.796463 | -0.908311 | -0.826426 | -0.357903 | -0.097872 | -0.481839 | -0.407004 | -0.301172 | -0.073540 | 0.528263 | -0.483765 | -0.427137 | 1.079402 | -0.026404 | -0.437263 | -0.450814 | 1.480432 | -0.905203 | -1.156909 | -1.549350 | -1.369057 | -1.225051 | 0.679937 | -1.255360 | -0.565994 | -0.564945 | -0.612478 | -0.547354 | -0.490751 | 0.753047 | 0.140757 | 0.687299 | -0.481231 | -0.427624 | -0.625875 | -0.670050 | -0.498772 | -0.192632 | 0.434975 | 0.346052 | 1.019073 | -0.334539 | -0.268514 | -0.698952 | -0.675088 | -0.502388 | -0.233313 | 0.112064 | 0.312595 | -0.713846 | 0.036020 | -0.661584 | 0.703377 | -0.418799 | -0.204974 | 1.363395 | -0.435132 | -0.408812 | -0.208058 | -0.140325 | -0.35014 | -0.401058 | -0.356942 | -0.204598 | 0.132947 | -0.074673 | 0.025481 | 0.123964 | 0.039418 | -0.004210 | -0.110178 | 0.196399 | -0.027912 | 0.202106 | 0.884371 | 0.771104 | 0.368065 | 0.796750 | -0.297067 | -0.511371 | -1.096459 | -0.635847 | -1.206031 | -0.639811 | -0.444443 | -0.362055 | -0.262864 | 0.421563 | 1.141122 | 2.339941 | 0.308171 | 1.125327 | 0.512588 | -0.295718 | 1.144504 | 1.577384 | -0.099804 | 0.113996 | -0.814722 | -0.837017 | -0.859166 | -0.577640 | -0.419608 | -0.726033 | -0.245340 | -0.008552 | -0.830634 | -0.401284 | -0.256148 | 0.470604 | -0.550613 | -0.015137 | 0.361045 | -0.757709 | 0.532837 | -0.472421 | 1.611839 | 0.948807 | -0.085371 | -0.692609 | -0.173901 | -0.941065 | -0.624503 | -0.796496 | 0.105553 | -0.678052 | -0.222682 | -0.145707 | -0.237232 | -0.255253 | -0.175025 | -1.111063 | -1.033469 | -0.800469 | -0.203192 | 0.519058 | -0.077545 | -0.320792 | 0.122485 | 2.019175 | 0.097333 | -0.625598 | -0.280742 | -0.332656 | 0.651776 | -0.725231 | -0.366841 | -0.467122 | -0.195031 | -0.279237 | 0.293011 | -0.575576 | -0.203149 | -0.479825 | 1.242595 | 0.498406 | -0.250948 | -0.384928 | -0.770158 | -0.018369 | 0.223555 | 0.821277 | 0.532757 | -0.155552 | 0.074928 | -0.024225 | 0.010509 | 0.120392 | 0.202849 | -0.175811 | -0.364774 | -0.38569 | -1.466953 | -0.080219 | 0.196440 | 4.062978 | -0.144517 | 0.919110 | -2.138184 | 2.295362 | -1.539379 | -0.093157 | -0.272049 | 0.234751 | -0.420779 | 0.043207 | -0.320933 | 0.892292 | 0.707894 | 0.549621 | 0.256274 | -0.035562 | -0.03654 | 0.0 | -0.004697 | -0.253723 | -0.404434 | -0.333796 | -0.268587 | -0.334003 | 0.803195 | -0.28932 | 0.773613 | -0.215969 | 0.581083 | -0.245018 | 0.742026 | -0.309369 | -0.241026 | -0.251325 | 0.799094 | 1.398853 | 0.667214 | 0.827539 | 2.130961 | 2.055903 | -0.679923 | -0.162958 | -0.897898 | -0.343768 | -0.553160 | -1.464595 | 0.997642 | 2.006185 | 0.497455 | 0.0 | -0.125011 | -0.134606 | -0.732418 | -0.195915 | -0.309852 | -0.196628 | -0.367887 | 1.396488 | -0.344450 | -0.319305 | -0.853900 | -0.492918 | -1.487472 | -0.524857 | 1.576554 | -0.541803 | -0.591157 | 0.953982 | 1.317407 | -0.610267 | -1.203835 | -0.795329 | 0.041781 | 0.051518 | 0.0 | 0.004697 | 0.316734 | 0.534469 | 0.456322 | 0.348845 | 0.423778 | -1.663034 | 0.377492 | -1.772827 | 0.280293 | -1.606939 | 0.326546 | -1.988105 | 0.44144 | 0.297813 | 0.329249 | -1.914381 | -3.440912 | -2.126740 | 0.558753 | -0.107034 | 0.0 | 0.398588 | -0.266595 | 1.405878 | 0.417184 | AMH | NC | 27017 | 0 | R2 | U | M | 3 | 00 | 00 | X | L4E | S4E | S4E | S4E | S4E | S4F | S4F | S4F | S4F | S4F | S4F | S4F | S4F | S4F | S4D | S4D | S4D | S4D | S3D | L | E | X | X | X | C | 0 | |||||||||||||||||||||||||||||||||||
| 3 | -0.056484 | -0.339022 | -1.725610 | -0.480247 | -0.143194 | -0.210819 | -0.148904 | -0.401004 | -0.141417 | -0.339122 | -0.215411 | -0.157479 | -0.190095 | -0.220597 | -0.351784 | -0.2129 | -0.252319 | -0.050476 | 1.48172 | -0.222578 | -0.670013 | -1.072417 | -0.087578 | -0.901772 | -0.908471 | -0.023502 | -2.075803 | -0.462353 | -0.490013 | -0.477209 | -1.227379 | -0.182723 | 1.626640 | 1.179933 | -0.997831 | -1.160287 | -0.446136 | -0.224102 | 1.136617 | 1.772257 | 8.590218 | 0.705663 | -0.246320 | -0.243474 | -0.248958 | -0.200139 | -0.058664 | 2.270259 | -0.23121 | -0.102556 | -0.154776 | -0.303791 | -0.243766 | -0.137628 | -0.271910 | -0.264577 | -0.136507 | 0.026052 | 0.717347 | -0.667192 | -0.206748 | 0.558264 | 0.365828 | -0.655477 | 0.687266 | 0.020790 | -0.621911 | -0.081139 | 0.839642 | 0.237918 | -0.422407 | -1.484835 | 0.985022 | 0.055041 | 0.270098 | 0.081820 | 0.040072 | -0.861290 | 0.499238 | 0.390689 | 0.715413 | 1.104004 | 0.374252 | -0.401351 | -0.297151 | 0.021431 | 0.265375 | 0.465360 | 0.592856 | 0.637262 | 0.019164 | -0.649870 | -0.691025 | -0.645693 | 0.123877 | -0.314121 | 0.678020 | -0.068780 | 0.134259 | -0.970508 | -1.289143 | -1.074189 | 1.146616 | 0.226786 | -0.214236 | -0.368314 | -0.000842 | 0.073138 | 0.124028 | 0.172315 | 0.110960 | -0.066387 | -0.380719 | 1.254837 | -0.725716 | 1.141685 | -0.762920 | -0.208031 | -0.600414 | -1.077178 | -0.365232 | -0.433888 | -0.452631 | -0.293593 | -0.136434 | 0.121914 | 0.405410 | 0.483550 | 0.610424 | 0.196418 | 1.525465 | -0.195510 | 0.177533 | -0.401830 | 0.338784 | 0.528263 | -0.483765 | -0.550519 | 0.026897 | 4.234980 | -0.164641 | -0.627901 | 1.141587 | -0.874130 | -0.985117 | -1.305531 | -1.786439 | 2.033273 | -0.879364 | 1.696762 | 0.279235 | -0.000969 | 0.044784 | -0.054055 | -0.069497 | 0.398728 | -0.633571 | -1.939845 | 1.040721 | 0.618554 | -0.106148 | -0.670050 | -0.498772 | 0.469501 | 1.681436 | -1.226764 | -1.420177 | -1.065693 | 1.068114 | -0.092253 | -0.675088 | -0.502388 | 0.507435 | -0.350798 | 1.305900 | -1.014057 | 0.973066 | -0.143075 | 0.187062 | -0.936860 | -1.511218 | 3.508626 | -0.435132 | -0.408812 | -0.208058 | -0.140325 | -0.35014 | 0.457741 | -0.935108 | -0.364830 | -0.076928 | -1.035095 | -1.363859 | -1.012533 | -1.020149 | 0.316754 | 0.494476 | -0.269079 | -0.173922 | -0.646179 | -2.124129 | -1.117320 | -2.383871 | 0.796750 | 1.844760 | 0.357160 | -1.384964 | -1.458045 | -1.206031 | -1.731165 | -0.444443 | -0.930978 | 0.430536 | 7.760875 | 0.086959 | -1.096230 | -1.302021 | -1.313115 | 7.060147 | -0.295718 | -0.119739 | -1.402566 | -1.397680 | -1.199181 | -1.496779 | 1.030444 | -0.859166 | -0.577640 | 0.902805 | -0.726033 | -1.176586 | -0.989522 | -0.830634 | -0.401284 | -0.977745 | -0.947541 | -0.040784 | -0.391542 | 1.479687 | -1.510271 | -0.528925 | -0.472421 | 2.344825 | -0.119550 | -1.476134 | 0.889290 | 1.020418 | -1.149177 | -0.335146 | -1.091549 | -0.451858 | -0.678052 | -0.058003 | -1.413657 | -0.237232 | -0.255253 | -0.175025 | -0.516781 | -0.833538 | -0.800469 | -1.194471 | 2.305051 | -0.138618 | 0.474987 | -0.311938 | -1.060949 | -0.641171 | 0.343025 | -0.280742 | -0.332656 | -0.263125 | -0.725231 | -0.366841 | -0.467122 | 3.255771 | -0.279237 | -0.763291 | -0.575576 | -0.203149 | 2.325223 | 0.443237 | -1.972178 | 2.897800 | 0.226987 | -0.770158 | 0.159561 | -1.000259 | 0.632775 | -0.733731 | 1.131580 | -0.446748 | -0.144009 | -0.158715 | -0.226203 | -0.563112 | 0.597020 | -0.364774 | -0.38569 | -0.200138 | 1.242609 | -0.455084 | -0.476034 | -0.144517 | 1.014707 | -2.102904 | 2.295362 | -1.398766 | -0.566955 | -0.582831 | 2.274750 | -0.420779 | 0.043207 | 0.000635 | 1.009324 | 0.839274 | 0.549621 | 0.256274 | -0.035562 | -0.03654 | 0.0 | -0.004697 | -0.253723 | -0.404434 | -0.333796 | -0.268587 | 1.136209 | 0.688348 | -0.28932 | 0.908426 | -0.215969 | 0.349480 | 1.889509 | -0.342138 | -0.309369 | 0.972670 | 1.876846 | -0.401299 | -0.231453 | -0.361942 | 0.040874 | 0.800881 | 0.466101 | -0.679923 | -0.359357 | -0.538167 | -0.344741 | -0.614936 | 1.398672 | 0.997642 | 2.006185 | 0.707687 | 0.0 | -0.125011 | -0.134606 | -0.732418 | -0.195915 | -0.309852 | -0.196628 | -0.367887 | 1.396488 | -0.344450 | -0.319305 | -0.853900 | -0.492918 | -1.487472 | -0.524857 | -0.634621 | -0.541803 | -0.591157 | -1.048237 | -0.759348 | -0.610267 | 0.830703 | 1.257369 | 0.041781 | 0.051518 | 0.0 | 0.004697 | 0.316734 | 0.534469 | 0.456322 | 0.348845 | -2.364119 | -1.663034 | 0.377492 | -1.781399 | 0.280293 | -1.611042 | -3.059769 | 0.501695 | 0.44144 | -3.356203 | -3.035001 | 0.521229 | 0.290397 | 0.469795 | 1.490944 | -0.107034 | 0.0 | 1.904719 | -0.027132 | 0.016535 | 1.291582 | BRY | CA | 95953 | 0 | R2 | U | F | 3 | 00 | 00 | X | L4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S4E | S2D | S2D | A1D | A1D | A1D | A1D | L | E | X | X | X | C | 0 | ||||||||||||||||||||||||||||||||||
| 4 | -0.056484 | 1.344798 | -0.532986 | -1.305138 | 6.118405 | 2.880944 | -0.148904 | 6.784411 | -0.141417 | 6.405165 | 3.598216 | -0.157479 | -0.190095 | -0.220597 | 4.051111 | -0.2129 | 1.245665 | -0.050476 | 1.48172 | 0.005685 | -0.221711 | -1.409015 | 1.191994 | 4.439723 | -0.312207 | -0.272422 | -1.261301 | -0.134294 | -0.171046 | -0.223359 | 0.857892 | -0.438579 | -0.660485 | -0.462367 | 0.581116 | -4.010915 | 5.458257 | -0.224102 | -0.411650 | -0.471411 | -0.319811 | -0.178221 | -0.246320 | -0.243474 | -0.248958 | -0.200139 | -0.058664 | -0.456136 | -0.23121 | -0.102556 | -0.451870 | -0.172954 | 0.410178 | 0.655525 | 0.032404 | 0.207622 | 0.337646 | 0.310313 | -0.771510 | 0.805212 | 0.420862 | 0.365376 | -0.176526 | -1.337021 | 0.196446 | 2.038266 | 0.278189 | -0.414455 | -0.706693 | -0.388555 | 0.465463 | -0.226832 | 0.985022 | 0.551008 | -0.322464 | 0.416194 | -0.595645 | -0.990554 | 1.005043 | 0.954417 | 2.164537 | 2.730481 | -1.348514 | 1.471580 | 0.371244 | 1.256584 | 1.014269 | 1.312241 | 1.172748 | 1.225094 | -0.545252 | -0.823188 | -0.736861 | -0.645693 | -0.361480 | -0.314121 | -0.190222 | -0.520403 | -0.573806 | -0.096426 | -0.393982 | 0.956763 | -0.955812 | 0.550987 | -0.622140 | -0.655420 | 0.483949 | 0.708067 | -0.648843 | -0.529932 | 0.744867 | -0.816887 | 2.319321 | 1.254837 | 2.328797 | -0.687354 | 0.479244 | -0.998607 | -2.415379 | -3.581202 | -1.543405 | 4.181111 | 5.365659 | 6.490636 | -0.511473 | -0.629937 | -0.905724 | -0.962894 | -0.244843 | -0.357903 | -0.393025 | -0.052346 | -0.114735 | -0.099855 | 0.751107 | 1.413800 | -0.803009 | -0.550519 | -0.604606 | -0.301331 | -0.709884 | -0.627901 | -0.552639 | -0.128389 | 0.446489 | 0.431676 | 0.258733 | 0.519234 | -0.442177 | -1.169542 | -0.634865 | -0.811684 | -0.606158 | -0.660278 | -0.696992 | 0.186136 | 1.560359 | 1.179889 | -0.757950 | -1.264566 | -0.279391 | -0.670050 | -0.498772 | 0.028079 | 0.518073 | 1.581836 | 0.748045 | -0.578257 | -1.414195 | -0.243927 | -0.675088 | -0.502388 | 0.137061 | 0.652071 | 0.312595 | -1.914691 | 0.348369 | -1.828229 | 1.865085 | -0.833248 | -0.286614 | 1.363395 | -0.249003 | -0.179391 | -0.208058 | -0.140325 | -0.35014 | -0.186358 | -0.646025 | -0.044366 | -0.916428 | 0.725679 | 0.488595 | -0.444285 | 0.922391 | -0.325174 | -0.110178 | -0.424239 | -0.392939 | -0.337712 | 1.018082 | -1.117320 | 0.334505 | 0.796750 | 0.379300 | 0.357160 | -0.663701 | -0.635847 | -1.206031 | -0.094134 | 2.756718 | 3.051485 | 1.990686 | -0.173516 | -0.440122 | -1.096230 | 0.952248 | -0.616417 | -0.214919 | -0.295718 | -0.119739 | -1.601229 | 0.224664 | -0.323729 | -0.814722 | -0.837017 | -1.083507 | 0.795937 | 0.902805 | 1.179881 | 1.617151 | 4.111521 | -0.589543 | -0.401284 | 4.554498 | -0.339765 | -0.295698 | -0.203340 | -1.790189 | 1.499978 | 0.532837 | -0.472421 | 0.878853 | 0.948807 | 0.113310 | -1.124036 | -1.069640 | -0.212676 | -0.335146 | -0.501443 | 0.523611 | -0.678052 | 0.436034 | 0.065617 | 0.222889 | 0.013568 | 1.247998 | -0.120593 | -0.333710 | 1.720402 | -1.548499 | -0.216351 | 1.204985 | 0.872877 | -0.311938 | -1.297882 | -0.641171 | -1.230987 | -0.280742 | -0.332656 | -1.482994 | -0.725231 | -0.366841 | -0.467122 | -0.195031 | -0.279237 | -0.763291 | -0.575576 | -0.203149 | -0.583716 | 0.349194 | 0.683700 | -0.499533 | -0.384928 | -0.770158 | -0.196298 | -0.889003 | -0.215483 | 4.585521 | 0.809797 | -0.446748 | -0.683034 | -0.835613 | -1.265990 | -0.946093 | 0.983435 | -0.364774 | -0.38569 | -1.213590 | 0.581195 | 1.535683 | -0.166556 | -0.144517 | -0.514837 | 0.578396 | -0.536019 | -1.426889 | 0.143742 | 0.142326 | -0.639534 | -0.420779 | 0.405784 | 1.608474 | 2.881823 | 2.897566 | 3.955559 | 2.729494 | -0.035562 | -0.03654 | 0.0 | -0.004697 | -0.253723 | 1.312009 | -0.333796 | -0.268587 | -0.334003 | -0.460123 | -0.28932 | 0.908426 | -0.215969 | -0.461129 | -0.245018 | -0.342138 | -0.309369 | -0.241026 | -0.251325 | -0.401299 | -0.231453 | -0.361942 | 1.267395 | 3.340124 | 0.693215 | -0.566975 | -0.202238 | -0.178437 | -0.343118 | -0.610101 | -1.609433 | 0.997642 | 0.111907 | 1.268306 | 0.0 | -0.125011 | -0.134606 | -0.732418 | -0.195915 | -0.297045 | -0.196628 | -0.367887 | -0.715766 | -0.338515 | -0.319305 | -0.835355 | -0.492918 | 0.672282 | -0.524857 | -0.634621 | -0.537370 | -0.591157 | -1.048237 | -0.759348 | -0.648021 | -1.203835 | -0.795329 | 0.041781 | 0.051518 | 0.0 | 0.004697 | 0.316734 | -1.868237 | 0.456322 | 0.348845 | 0.423778 | 0.599951 | 0.377492 | -1.772827 | 0.280293 | 0.621161 | 0.326546 | 0.501695 | 0.44144 | 0.297813 | 0.329249 | 0.521229 | 0.290397 | 0.469795 | 4.021177 | -0.360909 | 0.0 | -0.323100 | 0.540018 | -0.678137 | 1.583049 | FL | 33176 | 0 | X | X | S2 | H | F | 3 | 00 | 12 | Y | Y | Y | Y | Y | Y | Y | 3 | L2F | A2F | A2F | A2F | A1D | I2D | A1E | A1E | L1D | A1E | A1E | L1D | L3D | L3D | A2D | A2D | A3D | A3D | A3D | I4E | A3D | A3D | L | F | X | X | X | A | 0 |
def apply_pca(df):
pca = PCA()
columns=df.select_dtypes(include='number').columns.tolist()
pca_feat=pca.fit_transform(df[columns])
cov_matrix = df[columns].cov()
#composing back the covariance matrix
df_pca=pd.DataFrame(pca.components_.T @ np.diag(pca.explained_variance_) @ pca.components_, index=cov_matrix.index, columns=cov_matrix.columns)
df_pca_f=pd.DataFrame({'Eigenvalue': pca.explained_variance_,'Difference': np.insert(np.diff(pca.explained_variance_), 0, 0),'Proportion': pca.explained_variance_ratio_,'Cumulative': np.cumsum(pca.explained_variance_ratio_)},index=range(1, pca.n_components_ + 1))
return pca, df_pca, df_pca_f
def plot_pca(pca):
#figure & axes
fig,(ax1,ax2)=plt.subplots(1,2,figsize=(30,15))
ax1.plot(pca.explained_variance_, marker='.', markersize=20)
ax2.plot(pca.explained_variance_ratio_, marker='.', markersize=20, label='Proportion')
ax2.plot(np.cumsum(pca.explained_variance_ratio_), marker='.', markersize=12, linestyle='--', label='Cumulative')
#customizations
ax2.legend()
ax1.set_title('Scree Plot', fontsize=18)
ax2.set_title('Variance Explained', fontsize=18)
ax1.set_ylabel('Eigenvalue', fontsize=18)
ax2.set_ylabel('Proportion', fontsize=18)
ax1.set_xlabel('Components', fontsize=18)
ax2.set_xlabel('Components', fontsize=18)
ax1.set_xticks(range(0, pca.n_components_, 2))
ax1.set_xticklabels(range(1, pca.n_components_ + 1, 2))
ax2.set_xticks(range(0, pca.n_components_, 2))
ax2.set_xticklabels(range(1, pca.n_components_ + 1, 2))
plt.show()
def color_pca_red_green(corr):
return 'background-color: red' if corr < -0.45 else 'background-color: green' if corr > 0.45 else ''
dic={}
for i in [1,4,7,8,9]:
dic['df'+str(i)],found=group.shift(i).add_suffix('df'+str(i)),False
dic['df'+str(i)]=data_ss.loc[:,group.loc[i,'Var'].split(',')]
dic['pca'+str(i)],dic['df_pca'+str(i)],dic['df_pca_f'+str(i)],dic['pctg_cum'+str(i)]='','','',''
dic['pca'+str(i)],dic['df_pca'+str(i)],dic['df_pca_f'+str(i)]=apply_pca(dic['df'+str(i)])
print('\nGroup: '+str.upper(group.loc[i,'Group']))
plot_pca(dic['pca'+str(i)])
for j in range(len(dic['pca'+str(i)].explained_variance_ratio_*100)):
dic['pctg_cum'+str(i)]=np.round(np.sum(dic['pca'+str(i)].explained_variance_ratio_[0:j+1])*100,2)
if dic['pctg_cum'+str(i)]<100:
print('Component PC{}, Cumulative Explained Ratio {}'.format(j,dic['pctg_cum'+str(i)]))
if dic['pctg_cum'+str(i)]>=86 and not(found):
dic['n_components'+str(i)],found=j,True
dic['pca'+str(i)]=PCA(n_components=dic['n_components'+str(i)])
dic['metric_cleaned'+str(i)]=dic['df_pca'+str(i)].select_dtypes(include='number').columns.tolist()
dic['pca_feat'+str(i)]=dic['pca'+str(i)].fit_transform(dic['df_pca'+str(i)][dic['metric_cleaned'+str(i)]])
dic['pca_feat_names'+str(i)]=[f'PC{z}' for z in range(dic['pca'+str(i)].n_components_)]
dic['pca_df'+str(i)]=pd.DataFrame(dic['pca_feat'+str(i)], index=dic['df_pca'+str(i)].index, columns=dic['pca_feat_names'+str(i)])
#reassigning dataframe to contain pca variables
dic['df_pca'+str(i)] = pd.concat([dic['df_pca'+str(i)], dic['pca_df'+str(i)]], axis=1)
Group: CHARACTERISTICS OF DONOR NEIGHBORHOOD
Component PC0, Cumulative Explained Ratio 14.02 Component PC1, Cumulative Explained Ratio 24.49 Component PC2, Cumulative Explained Ratio 33.14 Component PC3, Cumulative Explained Ratio 38.2 Component PC4, Cumulative Explained Ratio 42.67 Component PC5, Cumulative Explained Ratio 45.94 Component PC6, Cumulative Explained Ratio 48.41 Component PC7, Cumulative Explained Ratio 50.72 Component PC8, Cumulative Explained Ratio 52.67 Component PC9, Cumulative Explained Ratio 54.26 Component PC10, Cumulative Explained Ratio 55.7 Component PC11, Cumulative Explained Ratio 56.96 Component PC12, Cumulative Explained Ratio 58.13 Component PC13, Cumulative Explained Ratio 59.19 Component PC14, Cumulative Explained Ratio 60.2 Component PC15, Cumulative Explained Ratio 61.2 Component PC16, Cumulative Explained Ratio 62.14 Component PC17, Cumulative Explained Ratio 63.04 Component PC18, Cumulative Explained Ratio 63.91 Component PC19, Cumulative Explained Ratio 64.65 Component PC20, Cumulative Explained Ratio 65.33 Component PC21, Cumulative Explained Ratio 65.99 Component PC22, Cumulative Explained Ratio 66.64 Component PC23, Cumulative Explained Ratio 67.26 Component PC24, Cumulative Explained Ratio 67.85 Component PC25, Cumulative Explained Ratio 68.43 Component PC26, Cumulative Explained Ratio 68.99 Component PC27, Cumulative Explained Ratio 69.52 Component PC28, Cumulative Explained Ratio 70.02 Component PC29, Cumulative Explained Ratio 70.52 Component PC30, Cumulative Explained Ratio 71.01 Component PC31, Cumulative Explained Ratio 71.47 Component PC32, Cumulative Explained Ratio 71.93 Component PC33, Cumulative Explained Ratio 72.38 Component PC34, Cumulative Explained Ratio 72.81 Component PC35, Cumulative Explained Ratio 73.24 Component PC36, Cumulative Explained Ratio 73.65 Component PC37, Cumulative Explained Ratio 74.05 Component PC38, Cumulative Explained Ratio 74.46 Component PC39, Cumulative Explained Ratio 74.84 Component PC40, Cumulative Explained Ratio 75.22 Component PC41, Cumulative Explained Ratio 75.6 Component PC42, Cumulative Explained Ratio 75.97 Component PC43, Cumulative Explained Ratio 76.33 Component PC44, Cumulative Explained Ratio 76.69 Component PC45, Cumulative Explained Ratio 77.04 Component PC46, Cumulative Explained Ratio 77.38 Component PC47, Cumulative Explained Ratio 77.72 Component PC48, Cumulative Explained Ratio 78.06 Component PC49, Cumulative Explained Ratio 78.39 Component PC50, Cumulative Explained Ratio 78.72 Component PC51, Cumulative Explained Ratio 79.05 Component PC52, Cumulative Explained Ratio 79.37 Component PC53, Cumulative Explained Ratio 79.69 Component PC54, Cumulative Explained Ratio 80.01 Component PC55, Cumulative Explained Ratio 80.32 Component PC56, Cumulative Explained Ratio 80.63 Component PC57, Cumulative Explained Ratio 80.94 Component PC58, Cumulative Explained Ratio 81.25 Component PC59, Cumulative Explained Ratio 81.55 Component PC60, Cumulative Explained Ratio 81.85 Component PC61, Cumulative Explained Ratio 82.15 Component PC62, Cumulative Explained Ratio 82.45 Component PC63, Cumulative Explained Ratio 82.74 Component PC64, Cumulative Explained Ratio 83.02 Component PC65, Cumulative Explained Ratio 83.31 Component PC66, Cumulative Explained Ratio 83.59 Component PC67, Cumulative Explained Ratio 83.87 Component PC68, Cumulative Explained Ratio 84.14 Component PC69, Cumulative Explained Ratio 84.41 Component PC70, Cumulative Explained Ratio 84.68 Component PC71, Cumulative Explained Ratio 84.94 Component PC72, Cumulative Explained Ratio 85.2 Component PC73, Cumulative Explained Ratio 85.46 Component PC74, Cumulative Explained Ratio 85.72 Component PC75, Cumulative Explained Ratio 85.97 Component PC76, Cumulative Explained Ratio 86.22 Component PC77, Cumulative Explained Ratio 86.47 Component PC78, Cumulative Explained Ratio 86.71 Component PC79, Cumulative Explained Ratio 86.95 Component PC80, Cumulative Explained Ratio 87.19 Component PC81, Cumulative Explained Ratio 87.42 Component PC82, Cumulative Explained Ratio 87.65 Component PC83, Cumulative Explained Ratio 87.88 Component PC84, Cumulative Explained Ratio 88.1 Component PC85, Cumulative Explained Ratio 88.33 Component PC86, Cumulative Explained Ratio 88.55 Component PC87, Cumulative Explained Ratio 88.77 Component PC88, Cumulative Explained Ratio 88.99 Component PC89, Cumulative Explained Ratio 89.2 Component PC90, Cumulative Explained Ratio 89.42 Component PC91, Cumulative Explained Ratio 89.62 Component PC92, Cumulative Explained Ratio 89.83 Component PC93, Cumulative Explained Ratio 90.03 Component PC94, Cumulative Explained Ratio 90.24 Component PC95, Cumulative Explained Ratio 90.44 Component PC96, Cumulative Explained Ratio 90.64 Component PC97, Cumulative Explained Ratio 90.84 Component PC98, Cumulative Explained Ratio 91.03 Component PC99, Cumulative Explained Ratio 91.22 Component PC100, Cumulative Explained Ratio 91.41 Component PC101, Cumulative Explained Ratio 91.59 Component PC102, Cumulative Explained Ratio 91.77 Component PC103, Cumulative Explained Ratio 91.95 Component PC104, Cumulative Explained Ratio 92.13 Component PC105, Cumulative Explained Ratio 92.3 Component PC106, Cumulative Explained Ratio 92.47 Component PC107, Cumulative Explained Ratio 92.63 Component PC108, Cumulative Explained Ratio 92.8 Component PC109, Cumulative Explained Ratio 92.96 Component PC110, Cumulative Explained Ratio 93.12 Component PC111, Cumulative Explained Ratio 93.27 Component PC112, Cumulative Explained Ratio 93.43 Component PC113, Cumulative Explained Ratio 93.58 Component PC114, Cumulative Explained Ratio 93.73 Component PC115, Cumulative Explained Ratio 93.87 Component PC116, Cumulative Explained Ratio 94.02 Component PC117, Cumulative Explained Ratio 94.16 Component PC118, Cumulative Explained Ratio 94.3 Component PC119, Cumulative Explained Ratio 94.44 Component PC120, Cumulative Explained Ratio 94.57 Component PC121, Cumulative Explained Ratio 94.71 Component PC122, Cumulative Explained Ratio 94.84 Component PC123, Cumulative Explained Ratio 94.97 Component PC124, Cumulative Explained Ratio 95.1 Component PC125, Cumulative Explained Ratio 95.22 Component PC126, Cumulative Explained Ratio 95.34 Component PC127, Cumulative Explained Ratio 95.47 Component PC128, Cumulative Explained Ratio 95.59 Component PC129, Cumulative Explained Ratio 95.7 Component PC130, Cumulative Explained Ratio 95.82 Component PC131, Cumulative Explained Ratio 95.93 Component PC132, Cumulative Explained Ratio 96.04 Component PC133, Cumulative Explained Ratio 96.15 Component PC134, Cumulative Explained Ratio 96.26 Component PC135, Cumulative Explained Ratio 96.37 Component PC136, Cumulative Explained Ratio 96.47 Component PC137, Cumulative Explained Ratio 96.57 Component PC138, Cumulative Explained Ratio 96.67 Component PC139, Cumulative Explained Ratio 96.77 Component PC140, Cumulative Explained Ratio 96.86 Component PC141, Cumulative Explained Ratio 96.96 Component PC142, Cumulative Explained Ratio 97.05 Component PC143, Cumulative Explained Ratio 97.15 Component PC144, Cumulative Explained Ratio 97.24 Component PC145, Cumulative Explained Ratio 97.32 Component PC146, Cumulative Explained Ratio 97.41 Component PC147, Cumulative Explained Ratio 97.49 Component PC148, Cumulative Explained Ratio 97.57 Component PC149, Cumulative Explained Ratio 97.65 Component PC150, Cumulative Explained Ratio 97.72 Component PC151, Cumulative Explained Ratio 97.8 Component PC152, Cumulative Explained Ratio 97.87 Component PC153, Cumulative Explained Ratio 97.94 Component PC154, Cumulative Explained Ratio 98.01 Component PC155, Cumulative Explained Ratio 98.07 Component PC156, Cumulative Explained Ratio 98.13 Component PC157, Cumulative Explained Ratio 98.2 Component PC158, Cumulative Explained Ratio 98.25 Component PC159, Cumulative Explained Ratio 98.31 Component PC160, Cumulative Explained Ratio 98.37 Component PC161, Cumulative Explained Ratio 98.43 Component PC162, Cumulative Explained Ratio 98.48 Component PC163, Cumulative Explained Ratio 98.53 Component PC164, Cumulative Explained Ratio 98.58 Component PC165, Cumulative Explained Ratio 98.63 Component PC166, Cumulative Explained Ratio 98.68 Component PC167, Cumulative Explained Ratio 98.73 Component PC168, Cumulative Explained Ratio 98.77 Component PC169, Cumulative Explained Ratio 98.82 Component PC170, Cumulative Explained Ratio 98.86 Component PC171, Cumulative Explained Ratio 98.9 Component PC172, Cumulative Explained Ratio 98.94 Component PC173, Cumulative Explained Ratio 98.98 Component PC174, Cumulative Explained Ratio 99.02 Component PC175, Cumulative Explained Ratio 99.05 Component PC176, Cumulative Explained Ratio 99.09 Component PC177, Cumulative Explained Ratio 99.12 Component PC178, Cumulative Explained Ratio 99.16 Component PC179, Cumulative Explained Ratio 99.19 Component PC180, Cumulative Explained Ratio 99.22 Component PC181, Cumulative Explained Ratio 99.26 Component PC182, Cumulative Explained Ratio 99.29 Component PC183, Cumulative Explained Ratio 99.31 Component PC184, Cumulative Explained Ratio 99.34 Component PC185, Cumulative Explained Ratio 99.37 Component PC186, Cumulative Explained Ratio 99.4 Component PC187, Cumulative Explained Ratio 99.42 Component PC188, Cumulative Explained Ratio 99.45 Component PC189, Cumulative Explained Ratio 99.47 Component PC190, Cumulative Explained Ratio 99.49 Component PC191, Cumulative Explained Ratio 99.51 Component PC192, Cumulative Explained Ratio 99.53 Component PC193, Cumulative Explained Ratio 99.55 Component PC194, Cumulative Explained Ratio 99.57 Component PC195, Cumulative Explained Ratio 99.59 Component PC196, Cumulative Explained Ratio 99.61 Component PC197, Cumulative Explained Ratio 99.63 Component PC198, Cumulative Explained Ratio 99.64 Component PC199, Cumulative Explained Ratio 99.66 Component PC200, Cumulative Explained Ratio 99.68 Component PC201, Cumulative Explained Ratio 99.69 Component PC202, Cumulative Explained Ratio 99.71 Component PC203, Cumulative Explained Ratio 99.72 Component PC204, Cumulative Explained Ratio 99.73 Component PC205, Cumulative Explained Ratio 99.75 Component PC206, Cumulative Explained Ratio 99.76 Component PC207, Cumulative Explained Ratio 99.77 Component PC208, Cumulative Explained Ratio 99.78 Component PC209, Cumulative Explained Ratio 99.8 Component PC210, Cumulative Explained Ratio 99.81 Component PC211, Cumulative Explained Ratio 99.82 Component PC212, Cumulative Explained Ratio 99.83 Component PC213, Cumulative Explained Ratio 99.84 Component PC214, Cumulative Explained Ratio 99.85 Component PC215, Cumulative Explained Ratio 99.86 Component PC216, Cumulative Explained Ratio 99.86 Component PC217, Cumulative Explained Ratio 99.87 Component PC218, Cumulative Explained Ratio 99.88 Component PC219, Cumulative Explained Ratio 99.89 Component PC220, Cumulative Explained Ratio 99.9 Component PC221, Cumulative Explained Ratio 99.9 Component PC222, Cumulative Explained Ratio 99.91 Component PC223, Cumulative Explained Ratio 99.92 Component PC224, Cumulative Explained Ratio 99.92 Component PC225, Cumulative Explained Ratio 99.93 Component PC226, Cumulative Explained Ratio 99.93 Component PC227, Cumulative Explained Ratio 99.94 Component PC228, Cumulative Explained Ratio 99.94 Component PC229, Cumulative Explained Ratio 99.95 Component PC230, Cumulative Explained Ratio 99.95 Component PC231, Cumulative Explained Ratio 99.95 Component PC232, Cumulative Explained Ratio 99.96 Component PC233, Cumulative Explained Ratio 99.96 Component PC234, Cumulative Explained Ratio 99.96 Component PC235, Cumulative Explained Ratio 99.97 Component PC236, Cumulative Explained Ratio 99.97 Component PC237, Cumulative Explained Ratio 99.97 Component PC238, Cumulative Explained Ratio 99.97 Component PC239, Cumulative Explained Ratio 99.97 Component PC240, Cumulative Explained Ratio 99.98 Component PC241, Cumulative Explained Ratio 99.98 Component PC242, Cumulative Explained Ratio 99.98 Component PC243, Cumulative Explained Ratio 99.98 Component PC244, Cumulative Explained Ratio 99.98 Component PC245, Cumulative Explained Ratio 99.98 Component PC246, Cumulative Explained Ratio 99.98 Component PC247, Cumulative Explained Ratio 99.99 Component PC248, Cumulative Explained Ratio 99.99 Component PC249, Cumulative Explained Ratio 99.99 Component PC250, Cumulative Explained Ratio 99.99 Component PC251, Cumulative Explained Ratio 99.99 Component PC252, Cumulative Explained Ratio 99.99 Component PC253, Cumulative Explained Ratio 99.99 Component PC254, Cumulative Explained Ratio 99.99 Component PC255, Cumulative Explained Ratio 99.99 Component PC256, Cumulative Explained Ratio 99.99 Component PC257, Cumulative Explained Ratio 99.99 Component PC258, Cumulative Explained Ratio 99.99 Component PC259, Cumulative Explained Ratio 99.99 Group: GIVING HISTORY
Component PC0, Cumulative Explained Ratio 7.58 Component PC1, Cumulative Explained Ratio 12.95 Component PC2, Cumulative Explained Ratio 17.76 Component PC3, Cumulative Explained Ratio 22.51 Component PC4, Cumulative Explained Ratio 27.14 Component PC5, Cumulative Explained Ratio 31.69 Component PC6, Cumulative Explained Ratio 36.18 Component PC7, Cumulative Explained Ratio 40.63 Component PC8, Cumulative Explained Ratio 45.01 Component PC9, Cumulative Explained Ratio 49.3 Component PC10, Cumulative Explained Ratio 53.56 Component PC11, Cumulative Explained Ratio 57.61 Component PC12, Cumulative Explained Ratio 61.64 Component PC13, Cumulative Explained Ratio 65.61 Component PC14, Cumulative Explained Ratio 69.49 Component PC15, Cumulative Explained Ratio 73.19 Component PC16, Cumulative Explained Ratio 76.73 Component PC17, Cumulative Explained Ratio 80.17 Component PC18, Cumulative Explained Ratio 83.5 Component PC19, Cumulative Explained Ratio 86.48 Component PC20, Cumulative Explained Ratio 88.93 Component PC21, Cumulative Explained Ratio 90.56 Component PC22, Cumulative Explained Ratio 91.38 Component PC23, Cumulative Explained Ratio 92.07 Component PC24, Cumulative Explained Ratio 92.75 Component PC25, Cumulative Explained Ratio 93.32 Component PC26, Cumulative Explained Ratio 93.89 Component PC27, Cumulative Explained Ratio 94.44 Component PC28, Cumulative Explained Ratio 94.97 Component PC29, Cumulative Explained Ratio 95.47 Component PC30, Cumulative Explained Ratio 95.94 Component PC31, Cumulative Explained Ratio 96.41 Component PC32, Cumulative Explained Ratio 96.87 Component PC33, Cumulative Explained Ratio 97.32 Component PC34, Cumulative Explained Ratio 97.75 Component PC35, Cumulative Explained Ratio 98.17 Component PC36, Cumulative Explained Ratio 98.56 Component PC37, Cumulative Explained Ratio 98.94 Component PC38, Cumulative Explained Ratio 99.31 Component PC39, Cumulative Explained Ratio 99.66 Group: RESPONSE TO OTHER TYPES OF MAIL ORDERS
Component PC0, Cumulative Explained Ratio 33.09 Component PC1, Cumulative Explained Ratio 41.87 Component PC2, Cumulative Explained Ratio 48.98 Component PC3, Cumulative Explained Ratio 55.5 Component PC4, Cumulative Explained Ratio 61.76 Component PC5, Cumulative Explained Ratio 67.77 Component PC6, Cumulative Explained Ratio 73.59 Component PC7, Cumulative Explained Ratio 78.44 Component PC8, Cumulative Explained Ratio 83.08 Component PC9, Cumulative Explained Ratio 87.43 Component PC10, Cumulative Explained Ratio 90.98 Component PC11, Cumulative Explained Ratio 94.22 Component PC12, Cumulative Explained Ratio 97.05 Component PC13, Cumulative Explained Ratio 99.05 Group: SUMMARY VARIABLES OF GIVING HISTORY
Component PC0, Cumulative Explained Ratio 35.61 Component PC1, Cumulative Explained Ratio 58.44 Component PC2, Cumulative Explained Ratio 71.01 Component PC3, Cumulative Explained Ratio 79.48 Component PC4, Cumulative Explained Ratio 85.64 Component PC5, Cumulative Explained Ratio 90.38 Component PC6, Cumulative Explained Ratio 94.49 Component PC7, Cumulative Explained Ratio 96.72 Component PC8, Cumulative Explained Ratio 98.23 Component PC9, Cumulative Explained Ratio 99.2 Component PC10, Cumulative Explained Ratio 99.72 Group: SUMMARY VARIABLES OF PROMOTION HISTORY
Component PC0, Cumulative Explained Ratio 65.0 Component PC1, Cumulative Explained Ratio 88.75 Component PC2, Cumulative Explained Ratio 99.55
feat={}
for i in [1,4,7,8,9]:
print('\nGroup: '+str.upper(group.loc[i,'Group']) + ' - Most Relevant Features')
dic['print_df_pca'+str(i)]=dic['df_pca'+str(i)][dic['metric_cleaned'+str(i)] + dic['pca_feat_names'+str(i)]].corr().loc[dic['metric_cleaned'+str(i)], dic['pca_feat_names'+str(i)]].style.applymap(color_pca_red_green)
dic['most_important'+str(i)] = [np.abs(dic['pca'+str(i)].components_[j]).argmax() for j in range(dic['pca'+str(i)].n_components)]
metric_cleaned=dic['df'+str(i)].select_dtypes(include='number').columns.tolist()
dic['most_important_names'+str(i)] = list(dict.fromkeys([metric_cleaned[dic['most_important'+str(i)][j]] for j in range(dic['pca'+str(i)].n_components)]))
print(np.array(dic['most_important_names'+str(i)]))
plot_pca(dic['pca'+str(i)])
Group: CHARACTERISTICS OF DONOR NEIGHBORHOOD - Most Relevant Features ['IC3' 'HHD2' 'ETHC3' 'ETHC2' 'POP90C5' 'POBC1' 'ETH2' 'HHAS4' 'TPE10' 'ETH4' 'CHILC5' 'AFC1' 'POP902' 'DW9' 'ANC10' 'OEDC3' 'DW7' 'LSC4' 'EIC4' 'HUPA4' 'IC8' 'ETH12' 'HU4' 'ETH3' 'HC3' 'HC9' 'VC2' 'ETH15' 'PEC1' 'SEC1' 'ANC1' 'ANC3' 'IC17' 'IC18' 'HC15' 'EIC5' 'LFC8' 'ANC15' 'EIC6' 'TPE7' 'LFC9' 'EIC10' 'EIC12' 'ANC6' 'TPE6' 'OEDC7' 'ANC14' 'EIC7' 'ANC13' 'ETH11' 'SEC3']
Group: GIVING HISTORY - Most Relevant Features ['N_RDATE_15' 'N_RDATE_20' 'RAMNT_9' 'N_RDATE_6' 'N_RDATE_7' 'N_RDATE_3' 'RAMNT_12' 'RAMNT_7' 'RAMNT_11' 'RAMNT_17' 'RAMNT_14' 'N_RDATE_21' 'RAMNT_4' 'RAMNT_13' 'N_RDATE_19' 'RAMNT_23' 'RAMNT_18' 'RAMNT_24']
Group: RESPONSE TO OTHER TYPES OF MAIL ORDERS - Most Relevant Features ['MBBOOKS' 'MBGARDEN' 'PUBPHOTO' 'PUBOPP' 'MAGMALE' 'MBCOLECT' 'MBCRAFT' 'MAGFAML']
Group: SUMMARY VARIABLES OF GIVING HISTORY - Most Relevant Features ['N_FISTDATE' 'MAXRAMNT' 'N_LASTDATE' 'N_MAXRDATE']
Group: SUMMARY VARIABLES OF PROMOTION HISTORY - Most Relevant Features ['CARDPROM']
feat={}
for i in [1,4,7,8,9]:
print('\nGroup: '+str.upper(group.loc[i,'Group']) + ' - Most Relevant Features')
dic['print_df_pca'+str(i)]=dic['df_pca'+str(i)][dic['metric_cleaned'+str(i)] + dic['pca_feat_names'+str(i)]].corr().loc[dic['metric_cleaned'+str(i)], dic['pca_feat_names'+str(i)]].style.applymap(color_pca_red_green)
dic['most_important'+str(i)] = [np.abs(dic['pca'+str(i)].components_[j]).argmax() for j in range(dic['pca'+str(i)].n_components)]
metric_cleaned=dic['df'+str(i)].select_dtypes(include='number').columns.tolist()
dic['most_important_names'+str(i)] = list(dict.fromkeys([metric_cleaned[dic['most_important'+str(i)][j]] for j in range(dic['pca'+str(i)].n_components)]))
print(np.array(dic['most_important_names'+str(i)]))
plot_pca(dic['pca'+str(i)])
Group: CHARACTERISTICS OF DONOR NEIGHBORHOOD - Most Relevant Features ['IC3' 'HHD2' 'ETHC3' 'ETHC2' 'POP90C5' 'POBC1' 'ETH2' 'HHAS4' 'TPE10' 'ETH4' 'CHILC5' 'AFC1' 'POP902' 'DW9' 'ANC10' 'OEDC3' 'DW7' 'LSC4' 'EIC4' 'HUPA4' 'IC8' 'ETH12' 'HU4' 'ETH3' 'HC3' 'HC9' 'VC2' 'ETH15' 'PEC1' 'SEC1' 'ANC1' 'ANC3' 'IC17' 'IC18' 'HC15' 'EIC5' 'LFC8' 'ANC15' 'EIC6' 'TPE7' 'LFC9' 'EIC10' 'EIC12' 'ANC6' 'TPE6' 'OEDC7' 'ANC14' 'EIC7' 'ANC13' 'ETH11' 'SEC3']
Group: GIVING HISTORY - Most Relevant Features ['N_RDATE_15' 'N_RDATE_20' 'RAMNT_9' 'N_RDATE_6' 'N_RDATE_7' 'N_RDATE_3' 'RAMNT_12' 'RAMNT_7' 'RAMNT_11' 'RAMNT_17' 'RAMNT_14' 'N_RDATE_21' 'RAMNT_4' 'RAMNT_13' 'N_RDATE_19' 'RAMNT_23' 'RAMNT_18' 'RAMNT_24']
Group: RESPONSE TO OTHER TYPES OF MAIL ORDERS - Most Relevant Features ['MBBOOKS' 'MBGARDEN' 'PUBPHOTO' 'PUBOPP' 'MAGMALE' 'MBCOLECT' 'MBCRAFT' 'MAGFAML']
Group: SUMMARY VARIABLES OF GIVING HISTORY - Most Relevant Features ['N_FISTDATE' 'MAXRAMNT' 'N_LASTDATE' 'N_MAXRDATE']
Group: SUMMARY VARIABLES OF PROMOTION HISTORY - Most Relevant Features ['CARDPROM']
dic['print_df_pca1'] #CHARACTERISTICS OF DONOR NEIGHBORHOOD
| PC0 | PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | PC11 | PC12 | PC13 | PC14 | PC15 | PC16 | PC17 | PC18 | PC19 | PC20 | PC21 | PC22 | PC23 | PC24 | PC25 | PC26 | PC27 | PC28 | PC29 | PC30 | PC31 | PC32 | PC33 | PC34 | PC35 | PC36 | PC37 | PC38 | PC39 | PC40 | PC41 | PC42 | PC43 | PC44 | PC45 | PC46 | PC47 | PC48 | PC49 | PC50 | PC51 | PC52 | PC53 | PC54 | PC55 | PC56 | PC57 | PC58 | PC59 | PC60 | PC61 | PC62 | PC63 | PC64 | PC65 | PC66 | PC67 | PC68 | PC69 | PC70 | PC71 | PC72 | PC73 | PC74 | PC75 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| POP901 | 0.060254 | -0.047506 | -0.305926 | 0.096029 | -0.150930 | -0.155162 | 0.055072 | -0.131606 | 0.051293 | -0.152275 | 0.289044 | -0.129454 | 0.127545 | 0.255060 | 0.766950 | 0.020905 | -0.100458 | 0.074823 | 0.026046 | -0.023557 | -0.064989 | 0.019893 | -0.010395 | 0.020769 | -0.015975 | -0.004999 | -0.012103 | -0.025685 | 0.021165 | -0.008401 | -0.020014 | 0.014338 | -0.004521 | -0.011019 | -0.008812 | -0.018100 | -0.006590 | -0.008695 | 0.004870 | 0.008370 | -0.001883 | -0.006024 | -0.000467 | -0.012940 | -0.017199 | 0.002027 | 0.008888 | 0.011342 | 0.004505 | 0.013555 | -0.007437 | 0.007746 | -0.011608 | -0.013730 | 0.000930 | 0.001158 | 0.010371 | -0.014561 | 0.011611 | -0.005589 | -0.011307 | 0.006261 | 0.005896 | -0.006337 | 0.003990 | 0.001648 | -0.011262 | -0.006483 | 0.004433 | -0.007584 | 0.005383 | -0.006058 | 0.006688 | 0.004643 | -0.003298 | -0.001294 |
| POP902 | 0.009962 | 0.036681 | -0.206466 | 0.131648 | -0.166183 | -0.180406 | 0.084771 | -0.123448 | 0.070065 | -0.163345 | 0.280178 | -0.128788 | 0.136305 | 0.268055 | 0.782891 | 0.003559 | -0.098281 | 0.073879 | 0.020064 | -0.023031 | -0.058854 | 0.021656 | -0.009405 | 0.026259 | -0.012262 | -0.003847 | -0.015424 | -0.022677 | 0.019925 | -0.008217 | -0.017163 | 0.014336 | -0.003169 | -0.010157 | -0.007767 | -0.014140 | -0.006862 | -0.008939 | 0.005594 | 0.007882 | -0.002611 | -0.007438 | -0.000996 | -0.011818 | -0.014822 | 0.004175 | 0.008704 | 0.010892 | 0.004036 | 0.013408 | -0.007000 | 0.007912 | -0.012275 | -0.011854 | -0.000237 | -0.000873 | 0.010332 | -0.013203 | 0.010079 | -0.005087 | -0.010748 | 0.006580 | 0.004898 | -0.006625 | 0.002864 | 0.001741 | -0.011617 | -0.006578 | 0.005697 | -0.007598 | 0.004825 | -0.005025 | 0.006368 | 0.005114 | -0.002008 | -0.001202 |
| POP903 | 0.119390 | -0.222958 | -0.189964 | 0.158536 | -0.145605 | -0.146024 | 0.051242 | -0.142041 | 0.076014 | -0.139385 | 0.279170 | -0.120647 | 0.121303 | 0.255958 | 0.764513 | 0.003859 | -0.095584 | 0.077352 | 0.020610 | -0.019037 | -0.066571 | 0.017814 | -0.006809 | 0.025845 | -0.013205 | -0.010896 | -0.010438 | -0.028917 | 0.019081 | -0.002770 | -0.017524 | 0.016972 | -0.005793 | -0.012165 | -0.008616 | -0.017835 | -0.004989 | -0.009720 | 0.003261 | 0.011272 | -0.003053 | -0.005816 | 0.001889 | -0.011058 | -0.017325 | 0.002727 | 0.007312 | 0.010068 | 0.004807 | 0.012323 | -0.005337 | 0.007521 | -0.012700 | -0.013429 | 0.000486 | -0.001305 | 0.010005 | -0.012126 | 0.011009 | -0.004025 | -0.010736 | 0.005048 | 0.004142 | -0.004537 | 0.003155 | 0.001577 | -0.011491 | -0.006080 | 0.004590 | -0.005249 | 0.005019 | -0.005884 | 0.007939 | 0.002862 | -0.001283 | -0.001406 |
| POP90C1 | -0.490816 | -0.706104 | -0.324389 | -0.071197 | 0.290111 | -0.068910 | 0.115930 | 0.131049 | 0.031644 | -0.018956 | -0.025282 | 0.070464 | -0.040035 | 0.015034 | -0.000236 | 0.005830 | 0.022259 | 0.002364 | 0.024183 | 0.019801 | -0.079483 | 0.028408 | 0.005192 | 0.015220 | 0.019519 | -0.002062 | -0.020267 | 0.004314 | 0.000301 | -0.039105 | 0.010725 | 0.029268 | -0.012125 | -0.032811 | 0.000658 | 0.007597 | 0.000119 | 0.005041 | -0.004817 | 0.011110 | 0.012310 | 0.036015 | -0.012641 | -0.002707 | 0.006242 | 0.003742 | 0.014377 | 0.002984 | 0.010822 | 0.013461 | -0.001217 | -0.014797 | 0.010362 | 0.003813 | -0.017154 | 0.007643 | 0.001299 | -0.004892 | 0.006948 | 0.028911 | 0.018251 | 0.014941 | 0.007353 | -0.013775 | -0.015188 | -0.002451 | -0.007164 | -0.011655 | -0.008112 | -0.009967 | -0.004007 | -0.006811 | -0.003870 | 0.004929 | -0.007215 | 0.007322 |
| POP90C2 | 0.642707 | 0.227487 | 0.279086 | 0.091524 | 0.121916 | 0.161911 | 0.054005 | -0.047188 | -0.324048 | -0.218708 | 0.030812 | -0.080138 | 0.211075 | -0.081388 | 0.021498 | -0.076142 | -0.103113 | -0.031668 | -0.069182 | -0.042246 | 0.194293 | -0.125855 | -0.036699 | -0.065756 | -0.052626 | -0.004166 | 0.046502 | -0.040439 | 0.007652 | 0.120866 | 0.021976 | -0.084157 | 0.046379 | 0.079776 | -0.000307 | -0.013582 | -0.027573 | -0.047396 | -0.014332 | -0.019181 | -0.047236 | -0.095682 | 0.044566 | -0.028500 | -0.032888 | -0.007126 | -0.024275 | 0.003553 | -0.027730 | -0.031475 | -0.008487 | 0.040054 | -0.025111 | 0.009857 | 0.057314 | -0.020408 | 0.006973 | -0.000565 | -0.024587 | -0.079807 | -0.041693 | -0.061900 | -0.002322 | 0.043225 | 0.050076 | -0.003733 | 0.002358 | 0.052068 | 0.017654 | 0.025187 | 0.024597 | 0.026422 | 0.004523 | -0.028755 | 0.006742 | -0.018961 |
| POP90C3 | 0.279828 | 0.797848 | 0.295763 | 0.090079 | -0.294180 | -0.022949 | -0.177716 | -0.186089 | 0.093590 | 0.117022 | 0.016957 | -0.055538 | -0.040097 | 0.017132 | -0.009402 | 0.029711 | 0.018293 | 0.009524 | -0.003168 | -0.003498 | 0.012927 | 0.018201 | 0.008798 | 0.010856 | -0.003737 | 0.004186 | 0.004819 | 0.012514 | -0.001617 | -0.002415 | -0.022640 | 0.001422 | -0.006001 | 0.006713 | -0.000191 | -0.004380 | 0.011926 | 0.014049 | 0.012484 | -0.004064 | 0.004405 | -0.003358 | -0.003251 | 0.015019 | 0.006733 | -0.001523 | -0.006832 | -0.005026 | -0.000854 | -0.002531 | 0.005017 | 0.000718 | -0.001430 | -0.008390 | -0.003833 | -0.000975 | -0.004376 | 0.006102 | 0.001864 | -0.001085 | -0.004170 | 0.008085 | -0.007903 | -0.001655 | -0.002667 | 0.004292 | 0.007028 | -0.008102 | 0.002061 | 0.001068 | -0.005407 | -0.002731 | 0.002825 | 0.005939 | 0.005684 | -0.001140 |
| POP90C4 | -0.483382 | 0.563851 | -0.155301 | 0.261304 | 0.372517 | -0.229013 | -0.220961 | -0.281833 | -0.059333 | 0.088599 | -0.037173 | 0.047385 | -0.022668 | 0.003442 | 0.016034 | 0.076950 | -0.019632 | -0.045536 | -0.019114 | 0.020185 | -0.014237 | -0.010161 | -0.020502 | 0.006445 | -0.036030 | -0.005974 | 0.001467 | 0.019610 | 0.031004 | 0.014667 | -0.005550 | 0.008427 | -0.008372 | -0.008621 | 0.008829 | -0.027950 | -0.007081 | -0.010856 | -0.005355 | 0.016014 | -0.023744 | -0.000761 | 0.010058 | 0.000140 | 0.002930 | -0.002976 | 0.004039 | 0.000937 | 0.015629 | 0.005304 | -0.006768 | -0.008116 | -0.000943 | 0.001294 | -0.009568 | -0.001623 | -0.003685 | 0.001473 | -0.009938 | -0.009905 | 0.015617 | -0.013287 | 0.004795 | -0.000512 | 0.009895 | 0.002445 | 0.000984 | -0.007645 | -0.018921 | -0.000706 | 0.006131 | -0.001501 | -0.000935 | -0.005468 | 0.005421 | -0.000428 |
| POP90C5 | 0.076916 | -0.091746 | 0.428082 | 0.197856 | 0.801017 | -0.179493 | 0.044544 | -0.245634 | 0.007949 | -0.059295 | 0.028462 | -0.097174 | 0.025967 | 0.006171 | -0.032755 | -0.029677 | 0.039339 | 0.037211 | -0.016213 | 0.007906 | 0.004984 | 0.002581 | 0.016514 | 0.012776 | 0.010402 | 0.004709 | 0.001137 | -0.010814 | -0.009521 | 0.000255 | 0.001190 | 0.003725 | -0.002465 | 0.019016 | -0.003807 | 0.018644 | 0.012203 | 0.012889 | 0.011512 | -0.004284 | 0.017385 | -0.003360 | -0.007564 | -0.002999 | 0.001627 | 0.002848 | -0.001510 | -0.000156 | -0.011009 | -0.000894 | 0.006687 | 0.006604 | 0.005923 | 0.001342 | 0.006155 | -0.003160 | 0.005090 | -0.001437 | 0.009104 | 0.010323 | -0.014089 | 0.013855 | -0.005464 | 0.000140 | -0.008485 | -0.005197 | -0.008029 | 0.005584 | 0.016914 | -0.002965 | -0.005107 | 0.003543 | 0.001828 | 0.003220 | -0.006513 | -0.003321 |
| ETH1 | -0.457610 | 0.195874 | 0.647707 | 0.484896 | 0.059501 | 0.021318 | -0.251629 | 0.017115 | -0.040425 | -0.125756 | -0.017991 | 0.045687 | 0.002874 | -0.018982 | -0.001201 | 0.039170 | -0.042673 | 0.035821 | -0.041450 | -0.009953 | -0.017171 | 0.006169 | 0.007868 | 0.017054 | 0.003632 | -0.001671 | -0.008990 | 0.003375 | -0.014735 | 0.009077 | 0.012165 | 0.009685 | 0.009224 | 0.001520 | -0.014671 | 0.012399 | 0.011179 | 0.007019 | -0.014841 | 0.003321 | -0.004218 | 0.003185 | -0.008493 | 0.009550 | -0.001174 | -0.007392 | 0.007003 | 0.006514 | 0.002196 | -0.000415 | 0.004738 | -0.001633 | -0.000095 | 0.001966 | 0.000636 | -0.000626 | -0.002666 | 0.004452 | -0.001914 | 0.002912 | 0.000328 | -0.000907 | -0.001726 | -0.007958 | 0.000341 | 0.003808 | -0.000892 | -0.004635 | 0.009058 | -0.000976 | 0.002402 | 0.000940 | -0.002199 | -0.007097 | -0.003466 | 0.003048 |
| ETH2 | 0.581620 | 0.014038 | -0.432372 | -0.318396 | 0.213904 | 0.076575 | 0.442327 | -0.219021 | 0.176633 | 0.142966 | -0.023259 | -0.045529 | -0.054916 | 0.016124 | 0.011813 | -0.018900 | 0.051490 | -0.033394 | 0.103377 | 0.009180 | 0.024904 | -0.014559 | -0.018819 | -0.005779 | 0.008717 | -0.009006 | 0.002473 | -0.004639 | -0.007578 | 0.006512 | -0.025540 | -0.024771 | 0.005304 | 0.008843 | 0.023969 | -0.017438 | -0.012865 | -0.006351 | -0.002898 | 0.002288 | -0.002556 | -0.002840 | 0.012996 | -0.011863 | -0.003823 | 0.001025 | 0.002376 | -0.005713 | -0.008350 | 0.011420 | 0.001421 | 0.001946 | -0.000356 | 0.003844 | 0.001422 | -0.003565 | -0.000225 | 0.000304 | -0.000468 | -0.000137 | -0.002610 | -0.005191 | 0.004500 | 0.001355 | -0.003013 | -0.001794 | -0.004362 | 0.000442 | -0.010129 | 0.002857 | -0.003437 | -0.002463 | 0.007483 | -0.001098 | 0.002290 | -0.004996 |
| ETH3 | 0.507389 | 0.261211 | -0.210086 | -0.088426 | -0.171731 | -0.008293 | -0.022669 | -0.116072 | -0.247827 | 0.041381 | -0.091131 | -0.058723 | -0.077237 | -0.070140 | 0.021458 | -0.025508 | -0.138107 | 0.069132 | -0.088090 | 0.192168 | -0.002058 | -0.069674 | 0.206673 | 0.031634 | -0.130994 | -0.011913 | -0.083655 | -0.059450 | 0.296509 | 0.046125 | 0.142688 | 0.017915 | -0.088482 | -0.014610 | 0.014773 | 0.114460 | -0.024151 | 0.034638 | 0.263760 | -0.103731 | 0.151662 | -0.047711 | 0.059235 | 0.016844 | 0.063668 | 0.094094 | -0.042645 | -0.013001 | 0.117867 | -0.073282 | 0.007963 | -0.008853 | 0.061079 | -0.086248 | -0.002706 | 0.094845 | -0.023447 | -0.067159 | -0.021286 | -0.033184 | 0.027283 | 0.035995 | 0.019373 | -0.013707 | 0.037023 | -0.026259 | 0.012205 | 0.023061 | -0.058366 | 0.009609 | -0.022395 | -0.005234 | -0.006755 | 0.077006 | 0.003347 | -0.018545 |
| ETH4 | -0.426007 | -0.467185 | -0.446392 | -0.350809 | -0.012297 | -0.207405 | -0.114313 | 0.108541 | -0.079465 | 0.259088 | 0.098731 | -0.134076 | 0.254028 | 0.067355 | -0.051811 | -0.082385 | -0.006277 | -0.104528 | -0.102118 | 0.000582 | -0.056251 | 0.007366 | 0.018739 | -0.005576 | -0.016342 | 0.043983 | 0.015297 | 0.021139 | 0.007627 | -0.010769 | -0.005839 | 0.011087 | -0.005647 | 0.000060 | -0.003647 | -0.008408 | 0.002463 | -0.008256 | -0.014073 | 0.000235 | 0.001684 | 0.003947 | -0.008222 | -0.011543 | 0.003821 | 0.006047 | -0.009928 | -0.003602 | -0.005908 | -0.001905 | -0.012518 | -0.000132 | 0.000633 | 0.008492 | -0.001079 | 0.002289 | 0.012487 | -0.003250 | 0.001292 | 0.003288 | -0.000576 | 0.002551 | -0.001960 | 0.001824 | 0.007972 | -0.003212 | 0.003004 | -0.005181 | -0.002505 | -0.004114 | 0.000600 | 0.004820 | -0.003798 | 0.003181 | -0.000461 | -0.000363 |
| ETH5 | 0.193996 | -0.128315 | -0.692754 | -0.346964 | 0.029448 | -0.398638 | -0.177120 | 0.089878 | -0.225177 | -0.166770 | 0.079270 | 0.097816 | -0.146166 | -0.012733 | 0.026105 | 0.024958 | 0.122783 | 0.036827 | -0.020466 | -0.034838 | 0.046589 | -0.000318 | -0.030666 | -0.024224 | -0.032652 | -0.007530 | 0.005618 | 0.032518 | -0.021020 | -0.024076 | 0.002365 | 0.012877 | -0.016742 | 0.013342 | -0.006405 | -0.020943 | 0.005249 | -0.010818 | 0.011664 | 0.006041 | -0.014139 | -0.000842 | -0.000796 | -0.002146 | -0.002053 | -0.006816 | -0.010146 | -0.008659 | -0.005383 | 0.001380 | -0.007754 | -0.001075 | 0.001215 | 0.002744 | -0.011963 | -0.010127 | -0.000362 | 0.005301 | 0.011043 | 0.001125 | -0.005902 | 0.006920 | -0.005922 | 0.015649 | -0.004176 | -0.002631 | 0.001185 | 0.008592 | -0.000407 | -0.006072 | 0.004766 | 0.010554 | -0.002108 | 0.007737 | 0.001397 | 0.001768 |
| ETH6 | -0.663337 | -0.438734 | -0.376860 | -0.157003 | -0.021187 | -0.056269 | -0.053743 | -0.000648 | 0.056436 | -0.019640 | 0.106901 | -0.095775 | 0.055049 | 0.029152 | -0.070917 | -0.039842 | -0.009866 | -0.074120 | -0.087601 | 0.114232 | -0.039160 | -0.030139 | -0.000165 | 0.060071 | 0.070436 | -0.059789 | -0.076511 | 0.048449 | 0.081427 | 0.005116 | -0.036184 | -0.056663 | 0.074249 | -0.010257 | 0.028122 | -0.022771 | -0.022047 | -0.108132 | -0.015489 | -0.053882 | -0.009680 | 0.029640 | -0.042496 | -0.047556 | -0.042667 | -0.011932 | -0.006963 | -0.050297 | 0.018061 | -0.013955 | -0.011555 | 0.021819 | -0.021817 | -0.005358 | 0.002598 | -0.068261 | -0.003508 | -0.005765 | -0.005263 | 0.017431 | 0.030472 | 0.023429 | -0.015297 | 0.049955 | -0.079732 | 0.020527 | -0.056860 | -0.053269 | -0.022197 | -0.031654 | -0.013181 | -0.039521 | -0.042838 | -0.023554 | -0.035152 | 0.029488 |
| ETH7 | -0.403135 | -0.427675 | -0.195708 | -0.348262 | -0.039895 | -0.146915 | -0.103930 | 0.087220 | -0.085768 | 0.357077 | 0.091342 | -0.124069 | 0.329169 | 0.069393 | -0.034714 | -0.119420 | 0.027757 | -0.107564 | -0.098828 | -0.014430 | -0.026567 | -0.024733 | 0.058291 | -0.029581 | -0.118065 | 0.206419 | 0.099344 | -0.010545 | -0.073213 | -0.033505 | 0.073021 | 0.055881 | -0.010554 | -0.041966 | 0.015790 | -0.057696 | -0.006356 | 0.050465 | -0.011742 | 0.010795 | -0.011368 | -0.009370 | 0.035540 | -0.003322 | 0.040617 | 0.003008 | -0.018198 | 0.031688 | 0.009397 | 0.021217 | -0.043082 | -0.024238 | 0.045133 | 0.032573 | -0.039140 | -0.026871 | -0.003886 | -0.037504 | 0.016994 | -0.006920 | -0.016016 | 0.005903 | -0.004570 | -0.000909 | 0.002353 | -0.019660 | -0.006495 | 0.008896 | -0.012756 | 0.004303 | 0.008374 | 0.004801 | 0.010340 | 0.012484 | 0.010425 | -0.018869 |
| ETH8 | -0.448376 | -0.533555 | -0.269678 | -0.414422 | -0.009634 | -0.130614 | -0.144319 | 0.053708 | -0.030425 | 0.234516 | 0.089001 | -0.125717 | 0.214848 | 0.052820 | -0.041336 | -0.049807 | 0.000590 | -0.115531 | -0.139433 | -0.034624 | -0.077693 | 0.009969 | 0.003584 | -0.007587 | 0.063665 | -0.051079 | -0.047996 | 0.034730 | 0.025525 | 0.012671 | -0.037475 | -0.010752 | -0.046899 | 0.039447 | -0.023984 | 0.009630 | 0.011674 | 0.023999 | -0.018387 | 0.033872 | 0.011584 | 0.014283 | 0.015895 | 0.016062 | 0.001041 | 0.000724 | -0.018938 | 0.001088 | 0.016280 | -0.009916 | 0.026432 | 0.007492 | -0.021500 | 0.030255 | -0.024853 | 0.008056 | 0.006260 | 0.003831 | 0.010083 | -0.024616 | -0.006239 | -0.028382 | -0.004050 | -0.024855 | 0.010910 | -0.005450 | -0.022089 | 0.014950 | 0.019675 | 0.032517 | 0.010252 | 0.054891 | -0.004461 | 0.038091 | 0.006744 | -0.023793 |
| ETH9 | -0.330257 | -0.297109 | -0.549881 | -0.337603 | -0.010593 | -0.296823 | -0.090261 | 0.184544 | -0.094584 | 0.261399 | 0.100296 | -0.164172 | 0.221066 | 0.086067 | -0.054130 | -0.054422 | -0.014117 | -0.078439 | -0.073461 | -0.019042 | -0.021158 | -0.007071 | -0.006646 | -0.008914 | -0.032941 | 0.023561 | 0.022192 | 0.011511 | 0.012574 | -0.007522 | -0.013359 | 0.013814 | 0.003080 | -0.000135 | 0.000551 | 0.001124 | 0.003000 | -0.058189 | 0.026177 | -0.009551 | -0.008288 | -0.001262 | -0.058220 | -0.010132 | -0.018025 | 0.012720 | -0.002503 | -0.025963 | -0.037830 | -0.012232 | -0.006225 | 0.002769 | -0.000597 | -0.032966 | 0.029482 | 0.035444 | 0.011409 | 0.028970 | -0.001604 | 0.032821 | -0.003024 | -0.014372 | 0.005557 | 0.015172 | 0.003480 | 0.006016 | 0.027879 | -0.014054 | 0.001497 | -0.031906 | -0.043981 | -0.021362 | -0.045943 | -0.011647 | -0.031777 | 0.029432 |
| ETH10 | -0.503159 | -0.507886 | -0.352843 | -0.287726 | -0.032053 | -0.150402 | -0.114563 | 0.044064 | -0.041353 | 0.188081 | 0.101437 | -0.047908 | 0.217438 | 0.093319 | -0.058077 | -0.067950 | -0.010321 | -0.027817 | -0.074178 | 0.072132 | -0.045404 | -0.013625 | 0.021696 | -0.009313 | 0.025553 | -0.051398 | -0.054320 | 0.057375 | 0.008683 | 0.010127 | -0.064004 | -0.044464 | 0.042042 | 0.007316 | -0.002894 | 0.025247 | 0.020398 | 0.055240 | -0.042030 | -0.072310 | 0.010595 | -0.008135 | 0.016895 | -0.024009 | 0.035887 | 0.034926 | -0.008977 | 0.011198 | -0.011505 | 0.025576 | -0.085101 | -0.045134 | 0.003085 | 0.050314 | -0.024672 | -0.073990 | -0.014310 | -0.055060 | 0.032215 | -0.033871 | -0.006354 | 0.028861 | 0.001022 | 0.050077 | -0.088147 | 0.004336 | -0.022724 | -0.013330 | -0.007953 | -0.004841 | -0.002508 | -0.065970 | -0.028304 | -0.006499 | -0.000598 | -0.056688 |
| ETH11 | -0.198988 | -0.277842 | -0.619302 | -0.248506 | 0.046626 | -0.232174 | -0.113124 | 0.140370 | -0.067627 | 0.123109 | 0.067892 | -0.083033 | 0.196942 | -0.044850 | -0.062607 | -0.089801 | 0.014050 | -0.109430 | -0.029534 | 0.062914 | -0.094876 | 0.112327 | -0.032180 | 0.045690 | 0.074608 | -0.118187 | -0.045913 | 0.073096 | 0.138106 | -0.034961 | -0.099087 | 0.007423 | -0.042217 | 0.063472 | -0.029033 | 0.081489 | -0.011812 | -0.069888 | -0.066189 | 0.018360 | 0.030864 | 0.011784 | -0.020496 | -0.031390 | -0.022430 | -0.027794 | 0.012521 | -0.039306 | -0.039937 | 0.020010 | 0.047171 | 0.043267 | -0.063528 | -0.029512 | 0.080924 | 0.089727 | 0.077379 | 0.056382 | -0.069446 | 0.040212 | 0.050581 | 0.059601 | -0.027663 | -0.026476 | 0.123774 | 0.002091 | 0.061257 | -0.018149 | -0.027737 | -0.025093 | 0.092020 | 0.044941 | 0.118872 | -0.019417 | 0.069802 | 0.032397 |
| ETH12 | -0.056977 | -0.077024 | -0.222742 | -0.231359 | -0.077285 | -0.155294 | -0.040936 | 0.103350 | -0.110927 | 0.330571 | 0.093866 | -0.151051 | 0.317483 | 0.104652 | -0.058250 | -0.153222 | -0.016473 | -0.166303 | -0.105796 | -0.070838 | -0.039763 | -0.063232 | 0.113954 | -0.024442 | -0.248258 | 0.404989 | 0.260893 | -0.070581 | -0.125594 | -0.054849 | 0.151544 | 0.104349 | 0.039259 | -0.113746 | 0.027031 | -0.116911 | -0.005221 | -0.006729 | -0.007514 | 0.013012 | -0.024035 | -0.017290 | -0.014970 | -0.053220 | 0.028389 | 0.027340 | 0.009343 | 0.024320 | 0.011898 | -0.039032 | -0.061357 | 0.012915 | 0.084932 | -0.005916 | 0.015566 | 0.000922 | 0.027398 | -0.061016 | -0.007210 | 0.034377 | -0.017891 | 0.038396 | 0.021793 | -0.008861 | 0.078069 | -0.016617 | 0.045178 | -0.003022 | -0.019129 | -0.016559 | -0.011565 | -0.006636 | 0.037747 | -0.033929 | -0.006945 | 0.043736 |
| ETH13 | 0.237459 | -0.008831 | -0.684425 | -0.367583 | 0.043430 | -0.359795 | -0.188660 | 0.077203 | -0.256761 | -0.171049 | 0.042705 | 0.074911 | -0.111606 | -0.050223 | 0.012545 | 0.024320 | 0.094940 | 0.058733 | -0.010409 | 0.011432 | 0.053403 | 0.013736 | -0.072107 | -0.051203 | 0.000436 | -0.024701 | 0.046475 | -0.007875 | 0.008214 | -0.063408 | -0.018152 | 0.037816 | -0.053423 | -0.030112 | -0.013092 | -0.034917 | -0.001487 | -0.003078 | 0.027551 | 0.029212 | -0.030964 | 0.003626 | -0.013762 | 0.004745 | -0.005798 | -0.012110 | -0.019149 | -0.005325 | -0.009447 | 0.003867 | -0.017086 | 0.005182 | -0.019145 | 0.002039 | -0.016037 | -0.027244 | 0.007859 | -0.000831 | 0.013119 | -0.010886 | 0.002446 | 0.009530 | -0.013857 | 0.033688 | -0.004355 | -0.003508 | 0.000095 | 0.019543 | 0.009539 | -0.007792 | 0.004073 | 0.020946 | -0.011415 | 0.007603 | 0.002332 | 0.003868 |
| ETH14 | 0.179888 | -0.304340 | -0.553873 | -0.022666 | 0.028885 | -0.317751 | 0.067538 | 0.161764 | 0.026753 | -0.073701 | 0.066304 | 0.109219 | -0.161507 | 0.226469 | -0.034533 | 0.092163 | -0.019224 | -0.134643 | -0.075187 | -0.179922 | 0.059587 | -0.013216 | 0.083912 | 0.101179 | -0.029767 | 0.170627 | -0.073431 | 0.058357 | -0.039635 | 0.059529 | 0.078339 | -0.055411 | 0.082358 | 0.013620 | 0.039496 | -0.001559 | -0.021744 | -0.026763 | -0.075316 | 0.006737 | -0.011242 | 0.037812 | -0.000294 | -0.076231 | -0.017991 | 0.050309 | 0.057891 | 0.028311 | 0.029772 | -0.088557 | 0.013924 | 0.002359 | 0.095537 | -0.076899 | -0.036034 | 0.033082 | -0.021021 | 0.040848 | 0.065645 | 0.120663 | 0.012324 | 0.078251 | -0.084900 | 0.073329 | -0.018338 | 0.007481 | 0.036323 | 0.039446 | 0.019579 | -0.038465 | 0.116494 | -0.101979 | 0.090803 | 0.014059 | 0.086923 | -0.005709 |
| ETH15 | 0.034448 | -0.238386 | -0.251689 | -0.123777 | -0.021190 | -0.341811 | -0.071042 | 0.102895 | -0.008494 | -0.207393 | 0.254544 | 0.190936 | -0.256731 | 0.110752 | 0.058908 | 0.016782 | 0.267561 | -0.053631 | 0.000032 | -0.194780 | 0.011022 | -0.021136 | 0.117617 | 0.099046 | -0.172304 | 0.059403 | -0.171318 | 0.204826 | -0.148834 | 0.155674 | 0.112714 | -0.108036 | 0.105346 | 0.227221 | 0.037852 | 0.062017 | 0.023738 | -0.028366 | -0.072804 | -0.063858 | 0.064592 | -0.008913 | 0.041868 | -0.022949 | 0.001581 | 0.002595 | 0.021481 | -0.012109 | 0.009057 | 0.019204 | 0.022060 | -0.019831 | 0.090476 | 0.031984 | 0.020407 | 0.080052 | -0.028206 | -0.004352 | -0.024998 | 0.020897 | -0.026312 | -0.013087 | 0.073255 | -0.146754 | 0.045139 | -0.015417 | -0.009218 | -0.081337 | -0.053509 | 0.019898 | -0.016998 | 0.006896 | 0.006564 | -0.008181 | -0.054733 | -0.036658 |
| ETH16 | 0.017337 | -0.434738 | -0.625324 | -0.281879 | -0.015563 | -0.387306 | -0.155751 | 0.073162 | -0.161298 | -0.054362 | 0.084730 | 0.084550 | -0.142621 | 0.018383 | 0.059334 | -0.000839 | 0.123008 | 0.021578 | -0.048421 | -0.079714 | 0.009180 | -0.043843 | 0.044281 | -0.001192 | -0.073015 | -0.015423 | -0.045619 | 0.077671 | -0.053370 | 0.031188 | 0.004894 | -0.011429 | 0.050290 | 0.064172 | -0.011455 | -0.004998 | 0.025773 | -0.023633 | 0.008002 | -0.052678 | 0.017345 | -0.023755 | 0.028035 | 0.000477 | 0.015831 | -0.000583 | -0.002073 | -0.024732 | -0.002498 | 0.002794 | 0.011649 | -0.015999 | 0.010172 | 0.006387 | -0.001184 | 0.004329 | -0.013034 | 0.024087 | 0.003561 | 0.009871 | -0.029738 | -0.013329 | 0.005835 | 0.009137 | -0.024685 | 0.006965 | 0.001934 | 0.001716 | -0.016595 | -0.002399 | -0.010595 | -0.007724 | 0.009383 | 0.011629 | 0.007234 | 0.016323 |
| AGE901 | -0.059284 | -0.265516 | 0.925533 | -0.004237 | 0.152080 | -0.200557 | 0.036748 | -0.021574 | 0.007937 | 0.017315 | 0.024630 | -0.026737 | -0.012070 | 0.004692 | -0.020806 | -0.001452 | 0.004061 | 0.002252 | 0.007095 | -0.017167 | 0.006199 | 0.005727 | 0.003477 | 0.007700 | -0.008840 | -0.009541 | -0.007961 | -0.001893 | 0.006172 | -0.004043 | 0.000074 | 0.007674 | -0.004471 | 0.005777 | -0.000571 | -0.005277 | -0.003803 | -0.005115 | -0.003028 | -0.000279 | 0.001315 | -0.005242 | 0.005679 | -0.001056 | -0.003772 | 0.004404 | 0.002844 | -0.000231 | 0.004217 | 0.001312 | 0.004549 | 0.002144 | -0.000980 | 0.001857 | -0.002617 | -0.003589 | -0.000452 | -0.002506 | 0.000549 | 0.000243 | 0.002188 | 0.002704 | 0.005361 | -0.000806 | -0.003667 | -0.002044 | -0.000051 | 0.001223 | -0.001993 | 0.003987 | -0.000324 | -0.000425 | -0.000421 | -0.000153 | -0.002639 | -0.000623 |
| AGE902 | 0.087908 | -0.003546 | 0.941260 | -0.066607 | 0.221835 | -0.209550 | 0.039926 | -0.040240 | -0.015609 | -0.006475 | 0.024572 | -0.042781 | -0.010466 | 0.012014 | -0.024740 | -0.021050 | -0.003982 | 0.013660 | 0.006690 | -0.012273 | 0.006939 | 0.003165 | 0.002744 | 0.003731 | -0.010682 | -0.006168 | -0.010237 | -0.003729 | 0.005450 | -0.006780 | -0.001633 | 0.003944 | -0.001453 | 0.003743 | 0.001057 | -0.000331 | -0.003270 | -0.002626 | -0.003563 | -0.000083 | 0.003277 | -0.002873 | 0.003688 | -0.001296 | -0.004099 | 0.005626 | 0.001232 | 0.000541 | 0.001173 | 0.000795 | 0.005882 | 0.002303 | 0.002376 | 0.001878 | -0.001900 | -0.003191 | 0.000324 | -0.002117 | 0.001615 | 0.001329 | -0.000741 | 0.002997 | 0.002150 | -0.002486 | -0.003548 | -0.001829 | 0.000106 | -0.000003 | -0.000660 | 0.003876 | 0.000604 | -0.000602 | 0.000152 | 0.000777 | -0.002819 | -0.000130 |
| AGE903 | 0.241569 | -0.035957 | 0.902420 | -0.071264 | 0.271130 | -0.191239 | 0.027010 | -0.062256 | -0.029809 | -0.010517 | 0.048569 | -0.034518 | 0.003033 | 0.001570 | -0.022437 | 0.007376 | -0.006441 | 0.003727 | 0.010633 | 0.001153 | 0.004107 | 0.001116 | -0.005510 | 0.000831 | -0.009729 | -0.000841 | -0.006806 | -0.004186 | -0.001078 | -0.005654 | 0.001032 | -0.001647 | -0.003757 | 0.001337 | 0.000002 | 0.004823 | -0.005552 | -0.002714 | -0.004092 | -0.003467 | 0.006210 | -0.000920 | 0.001750 | -0.001704 | -0.003915 | 0.003866 | -0.001386 | 0.000316 | -0.000936 | 0.001766 | 0.006483 | 0.003286 | 0.003781 | -0.000369 | -0.000204 | -0.002970 | -0.000346 | -0.000744 | 0.002555 | 0.002804 | -0.001731 | 0.003812 | 0.000557 | -0.001977 | -0.003338 | -0.002385 | 0.000620 | -0.000367 | 0.000440 | 0.003617 | 0.000703 | -0.000084 | 0.000238 | 0.001355 | -0.002528 | 0.000478 |
| AGE904 | 0.158743 | -0.326397 | 0.883417 | 0.006301 | 0.232956 | -0.168795 | -0.008114 | -0.040803 | 0.004068 | 0.021774 | 0.028750 | -0.025594 | -0.000435 | -0.000862 | -0.011316 | 0.011412 | 0.012597 | 0.004299 | 0.007722 | -0.013221 | 0.006036 | 0.002085 | 0.000277 | 0.007623 | -0.008294 | -0.003807 | -0.005852 | -0.000606 | 0.006145 | -0.000349 | -0.000970 | 0.006625 | -0.003249 | 0.004838 | -0.000402 | -0.005254 | -0.002956 | -0.000624 | 0.000124 | 0.001518 | 0.001453 | -0.002074 | 0.002839 | -0.000798 | -0.002877 | 0.003620 | 0.000434 | -0.001353 | 0.001946 | 0.000693 | 0.002844 | 0.001724 | 0.001550 | 0.001370 | -0.000327 | -0.001490 | 0.000354 | -0.000617 | 0.000490 | 0.000430 | 0.001056 | 0.001420 | 0.002617 | -0.000441 | -0.001152 | -0.002187 | -0.000659 | 0.000613 | -0.001253 | 0.002393 | -0.000988 | 0.000393 | -0.000338 | -0.000140 | -0.001498 | 0.000078 |
| AGE905 | 0.174615 | -0.019882 | 0.905004 | -0.034300 | 0.317108 | -0.194186 | -0.006888 | -0.072373 | -0.025385 | -0.008579 | 0.008862 | -0.053614 | -0.004006 | 0.010692 | -0.015360 | -0.013628 | 0.001778 | 0.015672 | 0.004476 | -0.014962 | 0.005854 | 0.004572 | 0.006729 | 0.004834 | -0.010142 | -0.002336 | -0.008204 | -0.001988 | 0.006293 | -0.002617 | -0.002997 | 0.003020 | -0.000003 | 0.004365 | 0.002810 | -0.001481 | -0.000265 | 0.000257 | -0.001092 | 0.000994 | 0.002412 | -0.000531 | 0.002428 | -0.001502 | -0.002415 | 0.003707 | -0.001163 | -0.001727 | -0.000027 | 0.000055 | 0.003199 | 0.001642 | 0.001574 | 0.002144 | -0.001791 | -0.002351 | 0.001576 | -0.000371 | 0.000552 | 0.001215 | -0.001315 | 0.002134 | 0.000793 | -0.002158 | -0.001663 | -0.002021 | -0.000299 | -0.000311 | 0.000837 | 0.002624 | 0.000459 | -0.001007 | -0.000473 | 0.000499 | -0.001488 | 0.000490 |
| AGE906 | 0.279999 | -0.026042 | 0.857897 | -0.042024 | 0.364652 | -0.182604 | -0.017790 | -0.104219 | -0.038484 | -0.010141 | 0.037691 | -0.040714 | 0.007230 | 0.000399 | -0.013191 | 0.013198 | -0.003465 | 0.006185 | 0.007416 | -0.003141 | 0.004027 | 0.003973 | 0.000543 | 0.002723 | -0.007071 | 0.001509 | -0.004857 | -0.003226 | 0.000086 | -0.002137 | -0.000125 | -0.001938 | -0.002748 | 0.002196 | 0.001419 | 0.003006 | -0.002481 | -0.000666 | -0.001791 | -0.002401 | 0.004389 | 0.000103 | 0.000548 | -0.001729 | -0.002519 | 0.003182 | -0.003049 | -0.001545 | -0.001139 | 0.001077 | 0.004246 | 0.003081 | 0.002463 | 0.000740 | 0.000163 | -0.002246 | 0.001164 | 0.000867 | 0.001111 | 0.002419 | -0.002196 | 0.003122 | -0.000254 | -0.001765 | -0.001797 | -0.002527 | 0.000003 | -0.000488 | 0.001716 | 0.002526 | 0.000328 | -0.000720 | -0.000686 | 0.001209 | -0.001537 | 0.001514 |
| AGE907 | -0.152440 | 0.820537 | -0.515740 | -0.036605 | 0.107912 | -0.014068 | 0.014043 | -0.075681 | -0.059103 | -0.074805 | -0.040391 | -0.037701 | -0.010740 | 0.024955 | -0.013043 | -0.048336 | -0.033292 | 0.019864 | -0.006927 | 0.007760 | -0.004600 | 0.004627 | 0.016692 | -0.008128 | 0.005488 | 0.001859 | 0.005648 | -0.006119 | 0.000359 | -0.005956 | -0.002304 | -0.005283 | 0.000768 | -0.002426 | 0.005183 | 0.010075 | 0.006715 | 0.001186 | -0.002326 | -0.000602 | -0.000529 | 0.000696 | -0.001031 | -0.000832 | 0.001744 | -0.000402 | 0.000561 | 0.002127 | -0.004013 | -0.002396 | 0.000272 | -0.001285 | -0.000015 | 0.000530 | -0.001558 | -0.002493 | 0.001603 | -0.000527 | -0.000116 | 0.002060 | -0.005238 | 0.001407 | -0.004292 | -0.004183 | -0.000725 | 0.001774 | -0.000888 | -0.000781 | 0.005265 | -0.001240 | 0.002865 | -0.003906 | 0.001475 | 0.000205 | -0.000801 | 0.000083 |
| CHIL1 | 0.136481 | -0.593818 | -0.403921 | 0.428127 | 0.318554 | -0.176609 | -0.111028 | -0.043354 | 0.018462 | -0.067080 | -0.249141 | -0.142621 | 0.005200 | 0.039214 | 0.024877 | 0.083875 | 0.125705 | -0.045156 | -0.005994 | 0.084345 | -0.017022 | 0.016567 | -0.011879 | -0.014443 | -0.064487 | 0.027491 | -0.013493 | -0.021626 | 0.030803 | -0.011487 | 0.007509 | -0.023172 | -0.011184 | 0.011381 | -0.029328 | 0.014780 | -0.006235 | 0.013709 | -0.017355 | -0.010468 | -0.014721 | -0.025750 | -0.012122 | 0.010699 | -0.005221 | 0.013376 | 0.002707 | 0.000707 | -0.009327 | 0.016522 | 0.018398 | 0.016398 | -0.005467 | -0.001659 | -0.010998 | -0.014926 | 0.000782 | 0.004725 | 0.006568 | 0.006199 | -0.006396 | 0.005743 | 0.005008 | 0.004508 | -0.004326 | 0.001618 | 0.008165 | -0.005419 | -0.007042 | 0.005097 | 0.003627 | 0.002128 | 0.002996 | 0.000215 | -0.008093 | -0.004790 |
| CHIL2 | -0.288404 | 0.792806 | 0.281304 | 0.005430 | 0.331306 | -0.061927 | -0.029591 | -0.195017 | -0.093549 | 0.025939 | 0.066027 | -0.012997 | -0.017968 | -0.008560 | -0.008438 | -0.065986 | -0.087487 | 0.030178 | -0.028921 | -0.043375 | 0.001663 | -0.008352 | 0.034439 | 0.000870 | 0.036077 | -0.013953 | 0.021353 | 0.017881 | -0.030291 | 0.010727 | -0.025794 | 0.001838 | 0.020683 | -0.006864 | 0.056918 | -0.018989 | 0.002703 | -0.006939 | 0.004169 | 0.000693 | 0.027920 | 0.066447 | 0.027794 | -0.015102 | -0.013563 | -0.065694 | -0.015003 | 0.000297 | 0.013960 | -0.012842 | -0.033167 | -0.028641 | 0.001885 | -0.018370 | 0.005085 | 0.026303 | -0.021213 | 0.010004 | 0.000088 | -0.012046 | 0.012460 | -0.011382 | -0.002289 | 0.007967 | 0.005122 | 0.002658 | -0.006028 | 0.009773 | -0.004657 | -0.009488 | -0.011164 | 0.006882 | 0.002958 | 0.004790 | 0.005318 | -0.005438 |
| CHIL3 | -0.284097 | 0.447492 | 0.582695 | -0.248594 | 0.244119 | -0.048430 | 0.037775 | -0.221614 | 0.038414 | 0.112702 | 0.322973 | 0.209253 | 0.017895 | -0.045117 | -0.048405 | -0.000741 | -0.075170 | 0.025717 | 0.011804 | -0.054567 | 0.016101 | -0.025461 | -0.031607 | 0.043487 | 0.032964 | -0.029247 | -0.003052 | 0.022209 | 0.012264 | 0.020971 | 0.017190 | 0.049975 | -0.020742 | -0.000017 | -0.021834 | -0.010094 | 0.012013 | -0.012085 | 0.030632 | 0.030164 | -0.020129 | -0.050386 | -0.013881 | -0.001020 | 0.032157 | 0.065764 | 0.018496 | -0.000701 | 0.002176 | -0.006430 | 0.013440 | 0.009042 | 0.012057 | 0.030963 | 0.007622 | -0.015010 | 0.028925 | -0.021620 | -0.012507 | 0.006094 | -0.003686 | 0.005657 | -0.006131 | -0.018576 | 0.002051 | -0.009174 | -0.013105 | -0.006417 | 0.015474 | 0.000282 | 0.010123 | -0.010717 | -0.008372 | -0.009339 | 0.005613 | 0.011650 |
| AGEC1 | 0.356994 | -0.065717 | -0.841102 | 0.096337 | 0.161810 | 0.090480 | -0.071332 | -0.179213 | -0.060258 | 0.003660 | 0.134025 | 0.097807 | 0.051754 | -0.044650 | 0.009160 | 0.150066 | -0.020852 | -0.059271 | 0.012261 | 0.083960 | -0.011495 | -0.000451 | -0.033350 | -0.013524 | 0.027647 | 0.019059 | 0.031727 | -0.002498 | -0.028817 | 0.000667 | 0.015294 | -0.028409 | -0.020614 | -0.014251 | -0.010158 | 0.015113 | -0.016261 | -0.004820 | -0.003929 | -0.019177 | 0.003517 | 0.000684 | -0.010065 | 0.001045 | -0.001814 | -0.003072 | -0.005324 | 0.005369 | 0.001764 | 0.006018 | 0.005608 | 0.005330 | 0.006053 | -0.010742 | 0.015428 | 0.004430 | -0.004512 | 0.004388 | 0.002862 | 0.005953 | 0.000625 | 0.004089 | -0.004522 | 0.002263 | 0.000743 | -0.000550 | 0.000124 | 0.001624 | 0.002434 | -0.002358 | -0.000888 | 0.002061 | -0.000108 | 0.002375 | 0.000170 | 0.004939 |
| AGEC2 | -0.050786 | -0.061549 | -0.895172 | 0.379932 | 0.129552 | -0.019110 | -0.088214 | -0.017912 | 0.038135 | -0.011919 | -0.103095 | -0.053339 | 0.002482 | 0.020223 | 0.004475 | 0.004959 | 0.052820 | -0.003047 | -0.003921 | 0.017711 | -0.006338 | -0.012689 | -0.000431 | 0.001829 | 0.000669 | 0.001173 | 0.012745 | 0.015004 | 0.023394 | 0.009978 | -0.010186 | 0.011547 | -0.000806 | 0.003907 | -0.003971 | -0.012714 | 0.001808 | 0.008712 | 0.006613 | 0.011886 | -0.010086 | 0.001150 | -0.001359 | 0.002451 | 0.003609 | -0.001142 | 0.006644 | 0.003319 | 0.004321 | -0.000807 | -0.005011 | -0.005815 | 0.006650 | -0.001609 | -0.001112 | 0.005372 | 0.000886 | -0.005465 | -0.001064 | -0.000643 | 0.002935 | -0.004626 | -0.004203 | 0.000577 | 0.004377 | 0.003546 | -0.005054 | 0.002348 | -0.001431 | -0.006882 | -0.003345 | 0.001706 | 0.005017 | -0.002974 | 0.003273 | -0.007921 |
| AGEC3 | -0.815518 | 0.398854 | -0.370519 | 0.084505 | 0.035349 | 0.059805 | -0.004536 | -0.100937 | -0.006884 | 0.001257 | -0.033025 | -0.043751 | -0.028589 | -0.006167 | -0.009095 | -0.045899 | -0.025489 | 0.019844 | -0.018027 | -0.050681 | -0.014813 | -0.004629 | 0.034155 | 0.029586 | -0.011563 | -0.018445 | -0.007287 | -0.006233 | 0.000907 | 0.001768 | -0.002162 | 0.015481 | -0.001557 | 0.005014 | 0.013958 | -0.010490 | 0.018110 | -0.000367 | 0.001589 | 0.009456 | -0.003625 | -0.002881 | 0.007610 | -0.002316 | 0.004380 | -0.006309 | 0.004023 | -0.003074 | -0.002996 | -0.000566 | -0.003966 | -0.002713 | -0.010327 | 0.006872 | -0.009989 | -0.008979 | 0.000735 | 0.002728 | -0.000510 | -0.004906 | 0.002234 | -0.002203 | 0.005547 | 0.005104 | 0.000801 | -0.001393 | -0.002563 | 0.000822 | -0.001989 | -0.000128 | 0.001514 | -0.002170 | -0.002437 | -0.005601 | 0.000621 | -0.001070 |
| AGEC4 | -0.800406 | 0.502870 | 0.164924 | -0.142668 | 0.034324 | 0.026409 | -0.003485 | -0.152909 | 0.048466 | 0.063958 | 0.046373 | 0.116629 | -0.003548 | -0.011138 | -0.004870 | -0.036316 | -0.031311 | 0.037619 | -0.030399 | -0.018205 | 0.002731 | -0.003897 | -0.004585 | 0.003615 | -0.028524 | 0.001332 | -0.038773 | -0.001112 | 0.004605 | 0.001261 | 0.007019 | 0.007989 | 0.015182 | 0.004997 | -0.002410 | 0.005074 | 0.004435 | -0.004735 | -0.002775 | 0.004980 | 0.003465 | -0.007087 | -0.002138 | -0.002592 | -0.001177 | 0.007691 | 0.000347 | -0.003484 | -0.000242 | 0.000273 | -0.000744 | 0.004634 | -0.007138 | 0.006481 | -0.003677 | -0.004989 | 0.003462 | 0.001164 | -0.000600 | -0.005175 | -0.002274 | 0.000746 | 0.004994 | -0.002435 | -0.002909 | -0.001536 | 0.000239 | -0.008309 | -0.002820 | 0.004528 | 0.002847 | 0.003024 | -0.002165 | 0.003964 | -0.004419 | 0.001493 |
| AGEC5 | -0.003535 | 0.242094 | 0.899043 | -0.201547 | 0.127973 | -0.156555 | 0.046350 | -0.020680 | 0.008625 | 0.098101 | -0.010932 | 0.136758 | -0.021820 | 0.022298 | 0.035524 | -0.020034 | 0.008343 | -0.039036 | -0.054195 | 0.040687 | 0.019073 | 0.007671 | -0.056966 | -0.039283 | -0.033696 | 0.013083 | -0.015840 | 0.016729 | 0.015550 | 0.009916 | -0.005918 | -0.005335 | 0.025807 | 0.001680 | -0.001766 | 0.008314 | -0.004615 | 0.000837 | 0.008025 | 0.004707 | -0.000862 | 0.008557 | 0.004807 | -0.000216 | 0.004692 | -0.004786 | -0.007776 | -0.000988 | 0.001620 | 0.000949 | -0.006945 | -0.006202 | -0.000127 | 0.000562 | -0.004703 | 0.003726 | -0.001839 | 0.001058 | -0.006504 | 0.001322 | -0.000684 | -0.003801 | -0.001023 | -0.007916 | -0.001472 | 0.001400 | 0.007572 | -0.009584 | -0.005164 | -0.000249 | 0.006645 | 0.004138 | -0.003108 | 0.004745 | -0.003142 | 0.002495 |
| AGEC6 | 0.399738 | -0.156892 | 0.866099 | -0.075802 | 0.098625 | -0.194791 | 0.051351 | 0.050544 | -0.027786 | 0.009920 | -0.023984 | -0.008725 | -0.014765 | 0.020086 | 0.016228 | -0.004052 | 0.004841 | -0.039106 | -0.010969 | 0.016736 | 0.016084 | 0.014257 | -0.008431 | -0.005566 | 0.014228 | -0.005099 | 0.013893 | -0.005834 | -0.009384 | 0.004482 | 0.005058 | -0.004091 | -0.011223 | 0.000297 | 0.005381 | 0.001106 | -0.001595 | -0.010773 | 0.001128 | -0.004223 | -0.002692 | -0.002988 | 0.003960 | 0.000191 | 0.004975 | -0.001749 | -0.001980 | -0.000072 | 0.002377 | 0.000165 | 0.000369 | -0.002484 | 0.000987 | 0.000659 | -0.000038 | -0.000510 | -0.004040 | 0.001986 | -0.003583 | -0.002194 | 0.000074 | 0.001001 | -0.000036 | -0.000221 | -0.000402 | -0.001593 | 0.003305 | -0.000455 | -0.000524 | -0.000376 | 0.003382 | -0.002109 | -0.002000 | 0.000981 | 0.001305 | 0.001515 |
| AGEC7 | 0.586667 | -0.360459 | 0.674655 | -0.053591 | 0.145792 | -0.067476 | -0.016844 | 0.029677 | -0.033412 | -0.080096 | 0.050023 | -0.134437 | 0.021452 | -0.004653 | -0.042980 | 0.004164 | 0.002781 | 0.052729 | 0.056704 | -0.036835 | -0.002248 | 0.000112 | 0.028949 | 0.011800 | 0.002530 | 0.000501 | -0.005715 | -0.007097 | 0.001413 | -0.015927 | -0.005312 | -0.001136 | -0.003143 | 0.000978 | -0.002788 | -0.000001 | -0.005667 | 0.007814 | -0.007083 | -0.005389 | 0.009342 | 0.001798 | -0.002962 | -0.001058 | -0.011503 | 0.008962 | -0.000545 | -0.000990 | -0.003345 | -0.001082 | 0.009716 | 0.007591 | 0.005407 | -0.001533 | 0.003976 | -0.000692 | 0.004434 | -0.002605 | 0.006505 | 0.006557 | -0.002919 | 0.005291 | -0.000978 | -0.001355 | -0.002189 | -0.001892 | -0.002994 | 0.005444 | 0.005915 | 0.004931 | -0.005305 | -0.002534 | 0.002448 | -0.000226 | -0.001375 | 0.000675 |
| CHILC1 | 0.171538 | -0.720724 | -0.387234 | 0.363693 | 0.212313 | -0.134656 | -0.087246 | -0.014280 | 0.060853 | -0.036635 | -0.202094 | -0.099208 | 0.006455 | 0.036883 | 0.013086 | 0.067404 | 0.120844 | -0.023814 | -0.003508 | 0.071292 | -0.003384 | 0.010980 | -0.022630 | -0.001047 | -0.049020 | 0.016938 | -0.008311 | -0.017274 | 0.033990 | -0.004969 | 0.012000 | -0.003883 | -0.012585 | 0.011271 | -0.031027 | 0.002379 | -0.002623 | 0.018194 | -0.006614 | 0.003217 | -0.021215 | -0.029494 | -0.016073 | 0.009937 | 0.000112 | 0.025696 | 0.006569 | 0.001500 | -0.005397 | 0.008785 | 0.012564 | 0.011504 | -0.000403 | -0.001348 | -0.002636 | -0.008849 | 0.005421 | -0.000957 | 0.005921 | 0.005561 | -0.002106 | 0.003813 | 0.002906 | 0.003213 | -0.003382 | 0.002814 | 0.004596 | -0.006355 | -0.003590 | -0.000818 | -0.001250 | 0.000006 | 0.009368 | -0.003114 | -0.010835 | -0.010111 |
| CHILC2 | 0.023316 | -0.275238 | -0.416461 | 0.473033 | 0.406316 | -0.243087 | -0.114214 | -0.031309 | -0.024886 | -0.128997 | -0.369089 | -0.222358 | -0.004756 | 0.066632 | 0.037399 | 0.047182 | 0.138582 | -0.053061 | -0.022536 | 0.086431 | -0.023061 | 0.037204 | 0.017453 | -0.033283 | -0.088258 | 0.037943 | -0.030544 | -0.026290 | 0.034773 | -0.029803 | -0.006778 | -0.051241 | 0.001473 | 0.009823 | -0.027167 | 0.020532 | -0.010104 | 0.010702 | -0.029904 | -0.030222 | -0.010493 | -0.021530 | -0.007665 | 0.017806 | -0.016730 | 0.003580 | 0.003267 | -0.003524 | -0.011472 | 0.027697 | 0.029232 | 0.025383 | -0.012498 | 0.004788 | -0.025752 | -0.023307 | -0.002691 | 0.010160 | 0.004623 | 0.005605 | -0.013483 | 0.007273 | 0.010015 | 0.002387 | -0.004158 | -0.001028 | 0.011179 | -0.002707 | -0.013459 | 0.013353 | 0.015270 | 0.002628 | -0.011746 | 0.005147 | -0.000883 | 0.008567 |
| CHILC3 | -0.296814 | 0.770323 | 0.142531 | 0.133610 | 0.381286 | -0.111349 | -0.058751 | -0.162944 | -0.124146 | -0.022430 | -0.078653 | -0.105531 | -0.032557 | 0.020924 | 0.004755 | -0.093084 | -0.059295 | 0.030195 | -0.040752 | -0.026836 | -0.000176 | -0.000301 | 0.055618 | -0.013885 | 0.018394 | -0.003619 | 0.017576 | 0.015498 | -0.025740 | 0.000231 | -0.037590 | -0.011832 | 0.030079 | -0.006551 | 0.062836 | -0.020531 | -0.002589 | -0.002163 | -0.010207 | -0.008635 | 0.035161 | 0.084396 | 0.036227 | -0.013856 | -0.028218 | -0.089037 | -0.022372 | 0.001472 | 0.016123 | -0.010876 | -0.036906 | -0.034177 | -0.002710 | -0.027412 | 0.000750 | 0.033452 | -0.028218 | 0.016803 | 0.002187 | -0.016279 | 0.015281 | -0.014888 | -0.001619 | 0.013283 | 0.004390 | 0.005231 | -0.002803 | 0.010987 | -0.009562 | -0.008027 | -0.012700 | 0.011822 | 0.004884 | 0.008306 | 0.004543 | -0.008882 |
| CHILC4 | -0.325826 | 0.696055 | 0.452236 | -0.153689 | 0.226776 | -0.041916 | 0.018028 | -0.185991 | -0.020299 | 0.066132 | 0.196678 | 0.105159 | -0.002373 | -0.015895 | -0.035125 | -0.065285 | -0.083121 | 0.045778 | -0.017704 | -0.065060 | 0.017331 | -0.011526 | 0.005209 | 0.030243 | 0.039559 | -0.030016 | 0.004377 | 0.020165 | -0.007261 | 0.016673 | -0.004140 | 0.031959 | 0.004688 | -0.005703 | 0.016594 | -0.023173 | 0.009329 | -0.007416 | 0.025013 | 0.020717 | -0.004186 | 0.000807 | 0.001033 | -0.004947 | 0.012389 | 0.017438 | 0.008613 | -0.001131 | 0.010580 | -0.013354 | -0.008304 | -0.008092 | 0.010530 | 0.014805 | 0.008892 | 0.004829 | 0.013356 | -0.009894 | -0.007081 | -0.001532 | 0.002916 | -0.000648 | -0.005014 | -0.012862 | 0.007876 | -0.004690 | -0.012809 | 0.002131 | 0.008078 | -0.006210 | 0.000777 | -0.006545 | -0.008090 | -0.005292 | 0.007892 | 0.006431 |
| CHILC5 | -0.060932 | 0.047020 | 0.561598 | -0.239332 | 0.301448 | -0.008550 | 0.010069 | -0.297409 | 0.050958 | 0.160716 | 0.472031 | 0.286366 | 0.050795 | -0.113457 | -0.035688 | 0.167932 | -0.078367 | -0.045935 | 0.055469 | -0.009576 | -0.016783 | -0.045885 | -0.077112 | 0.037692 | 0.027372 | -0.012832 | 0.010665 | 0.013194 | -0.000262 | 0.033656 | 0.042048 | 0.040395 | -0.051543 | 0.007552 | -0.037331 | 0.028440 | 0.010709 | -0.023591 | 0.024667 | 0.022429 | -0.014388 | -0.070043 | -0.018629 | -0.007875 | 0.046755 | 0.064227 | 0.012030 | 0.001213 | -0.013635 | 0.005905 | 0.023037 | 0.020844 | 0.007727 | 0.023304 | 0.005492 | -0.032374 | 0.018678 | -0.017983 | -0.008915 | 0.013428 | -0.009694 | 0.011488 | -0.004342 | -0.009638 | -0.006449 | -0.009393 | -0.005426 | -0.010840 | 0.015951 | 0.005916 | 0.010053 | -0.007554 | -0.000346 | -0.007912 | -0.000709 | 0.008279 |
| HHAGE1 | 0.529358 | -0.188848 | 0.779924 | -0.148453 | 0.150061 | -0.151720 | 0.006830 | 0.046013 | -0.022597 | -0.015672 | 0.010037 | -0.050703 | -0.000704 | 0.015071 | -0.000027 | 0.006168 | 0.014717 | -0.005882 | 0.005012 | -0.001587 | 0.010283 | 0.003744 | 0.003581 | 0.010957 | 0.008605 | -0.006729 | 0.011449 | -0.012697 | -0.019165 | 0.002921 | 0.003068 | -0.003359 | -0.017439 | -0.000755 | 0.006842 | 0.008160 | -0.002497 | -0.007664 | 0.000237 | -0.003720 | 0.009009 | -0.000511 | -0.002772 | -0.003986 | -0.000511 | 0.001858 | -0.002382 | -0.002849 | -0.005511 | -0.000978 | 0.004219 | 0.001775 | 0.003128 | -0.000658 | 0.002137 | -0.000161 | -0.001690 | -0.000923 | 0.001016 | 0.000689 | -0.001189 | 0.002497 | -0.001927 | -0.000177 | 0.001200 | -0.002506 | 0.001182 | 0.000172 | 0.002197 | 0.002355 | -0.001453 | -0.003639 | 0.000015 | -0.000029 | 0.000902 | 0.000079 |
| HHAGE2 | 0.706638 | -0.351040 | 0.565944 | -0.040729 | 0.168936 | -0.026234 | -0.036802 | 0.007761 | -0.007195 | -0.062160 | 0.026359 | -0.095775 | 0.024327 | 0.003649 | -0.027437 | -0.015258 | 0.005542 | 0.062462 | 0.007971 | -0.017290 | 0.002966 | -0.005531 | 0.007742 | 0.022625 | -0.005396 | -0.018350 | 0.003859 | -0.019872 | -0.026962 | -0.002946 | -0.001496 | 0.003203 | -0.022511 | -0.004123 | 0.007069 | 0.017755 | -0.000003 | -0.006817 | -0.001233 | 0.000581 | 0.021008 | 0.004490 | -0.006978 | -0.009620 | -0.006970 | 0.004933 | -0.000806 | -0.007894 | -0.016244 | -0.005181 | 0.005528 | 0.005555 | 0.002579 | -0.001699 | 0.000047 | -0.001794 | 0.000053 | -0.003271 | 0.008334 | 0.004487 | -0.003694 | 0.005544 | -0.004810 | 0.001320 | 0.000728 | -0.001739 | 0.001410 | -0.000159 | 0.006166 | 0.002492 | -0.001540 | -0.005783 | 0.002494 | -0.001242 | -0.001734 | -0.001490 |
| HHAGE3 | 0.548497 | -0.197692 | 0.777450 | -0.113378 | 0.140281 | -0.123033 | 0.002535 | 0.037275 | -0.024068 | -0.022277 | 0.004498 | -0.053841 | -0.000140 | 0.014495 | -0.000811 | 0.002933 | 0.011852 | 0.000353 | 0.006609 | 0.000808 | 0.009514 | 0.004223 | 0.003046 | 0.009049 | 0.009865 | -0.007549 | 0.014265 | -0.014365 | -0.018877 | 0.001832 | 0.003313 | -0.001614 | -0.018426 | -0.001709 | 0.006190 | 0.007394 | -0.002635 | -0.006719 | -0.000039 | -0.003009 | 0.008669 | -0.000477 | -0.001961 | -0.003220 | -0.000057 | 0.001792 | -0.002143 | -0.002241 | -0.004343 | -0.001365 | 0.004407 | 0.001982 | 0.002659 | -0.000904 | 0.001217 | -0.001476 | -0.002016 | -0.001082 | 0.001047 | 0.000769 | -0.001137 | 0.002829 | -0.002109 | 0.000394 | 0.000617 | -0.001734 | 0.001210 | 0.001042 | 0.002677 | 0.002467 | -0.000871 | -0.003858 | 0.000573 | 0.000122 | 0.001379 | -0.000002 |
| HHN1 | 0.608603 | -0.723908 | 0.178336 | 0.159922 | 0.154929 | 0.053680 | -0.071560 | -0.092784 | 0.020384 | 0.004931 | 0.002772 | -0.031782 | 0.005031 | -0.007283 | -0.011692 | -0.019094 | 0.016378 | 0.048943 | -0.011543 | -0.009969 | -0.004558 | -0.013605 | -0.000889 | 0.011182 | -0.015709 | -0.014503 | 0.002165 | -0.001780 | -0.003538 | 0.000633 | -0.004508 | 0.013306 | -0.013853 | -0.000244 | 0.008767 | -0.002149 | 0.002263 | -0.008912 | 0.005805 | 0.009204 | 0.009456 | 0.004502 | -0.001467 | -0.011144 | -0.002299 | 0.001815 | -0.002232 | -0.009692 | -0.010761 | -0.002769 | -0.004143 | 0.003040 | 0.002008 | -0.000002 | -0.000760 | 0.000726 | 0.003823 | -0.002167 | 0.006227 | 0.000185 | 0.001212 | 0.000754 | 0.001746 | 0.002751 | 0.003528 | -0.001682 | -0.000542 | 0.001250 | -0.002377 | -0.001681 | -0.000803 | -0.000567 | 0.000172 | -0.000416 | -0.000251 | -0.000966 |
| HHN2 | -0.190291 | -0.181594 | 0.887092 | 0.263251 | 0.061963 | -0.174680 | 0.019103 | -0.059554 | -0.035358 | 0.079931 | -0.064374 | 0.055729 | -0.012688 | -0.007631 | 0.051179 | 0.021698 | 0.014470 | -0.088824 | -0.012066 | 0.029301 | 0.020200 | 0.022984 | -0.033173 | -0.012503 | 0.022317 | 0.009751 | 0.000632 | 0.022942 | 0.011095 | 0.013580 | 0.011667 | -0.001780 | 0.015094 | 0.015786 | -0.005112 | -0.013645 | -0.003291 | 0.001229 | 0.000254 | -0.007519 | -0.012936 | -0.002593 | 0.007310 | 0.009072 | 0.013209 | -0.003544 | -0.005106 | 0.008231 | 0.022985 | 0.003267 | 0.000489 | -0.004412 | -0.004836 | 0.002991 | -0.000704 | -0.003562 | -0.003623 | 0.005559 | -0.012935 | -0.004398 | 0.003731 | -0.001460 | 0.003729 | -0.002295 | -0.004151 | -0.000517 | 0.002308 | -0.001054 | 0.002452 | -0.000603 | 0.006336 | 0.000983 | -0.006006 | 0.003181 | 0.006548 | 0.004768 |
| HHN3 | -0.470896 | 0.730202 | -0.459206 | -0.141696 | 0.089112 | -0.049885 | 0.010703 | -0.009557 | -0.011238 | -0.031154 | 0.023006 | -0.008488 | 0.001895 | 0.010805 | -0.015802 | 0.015396 | -0.014988 | -0.002085 | 0.006771 | 0.000951 | -0.006977 | -0.000853 | 0.013811 | 0.000471 | -0.002660 | 0.006744 | -0.001398 | -0.006359 | 0.002546 | -0.003128 | -0.002392 | -0.007089 | 0.002121 | -0.004482 | -0.003466 | 0.005351 | 0.000623 | 0.006706 | -0.003320 | -0.001472 | -0.003253 | -0.003235 | -0.001381 | 0.004175 | -0.002893 | 0.000039 | 0.004419 | 0.004107 | -0.000382 | 0.001668 | 0.002930 | -0.000796 | 0.001428 | -0.000714 | 0.000185 | 0.000018 | -0.001142 | -0.000671 | 0.000465 | 0.001742 | -0.002118 | 0.000005 | -0.003007 | -0.001268 | -0.000562 | 0.000958 | -0.001975 | -0.000930 | 0.000255 | 0.000792 | -0.001842 | 0.000367 | 0.002543 | -0.001509 | -0.002711 | -0.002034 |
| HHN4 | -0.424369 | 0.728968 | -0.477808 | -0.205973 | 0.064249 | -0.069480 | -0.009097 | 0.000343 | -0.035353 | -0.047175 | 0.035761 | -0.025067 | -0.017685 | 0.015706 | -0.024216 | 0.006198 | -0.026878 | 0.001551 | 0.013542 | 0.003013 | -0.007107 | 0.001678 | 0.013915 | -0.007365 | -0.001712 | 0.000581 | 0.008294 | -0.010532 | 0.002931 | -0.007588 | -0.004810 | -0.005764 | -0.005366 | -0.008674 | 0.000794 | 0.003660 | -0.000434 | 0.002934 | -0.002823 | 0.000883 | -0.000305 | -0.001912 | -0.001030 | 0.001927 | -0.006282 | 0.001287 | 0.003375 | 0.003062 | -0.003443 | 0.001025 | 0.002944 | 0.000560 | 0.002591 | -0.003699 | 0.003473 | 0.001484 | -0.000376 | -0.001301 | 0.003649 | 0.000783 | -0.001500 | -0.000868 | -0.002073 | -0.000939 | 0.002222 | 0.001790 | -0.002418 | 0.000046 | -0.001890 | 0.001798 | -0.003035 | -0.001927 | 0.003818 | -0.001862 | -0.002482 | -0.001477 |
| HHN5 | -0.134242 | 0.657534 | -0.602859 | -0.367113 | 0.078077 | -0.151858 | -0.042495 | 0.009408 | -0.071298 | -0.046951 | 0.045587 | -0.018879 | -0.052234 | 0.018345 | -0.025966 | 0.001973 | -0.025068 | -0.005295 | 0.028936 | 0.011479 | 0.000555 | 0.010084 | 0.007846 | -0.019465 | 0.002624 | 0.000007 | 0.028298 | -0.019021 | 0.015510 | -0.018173 | -0.004438 | -0.000430 | -0.017223 | -0.016209 | 0.003481 | 0.000615 | -0.004325 | -0.001312 | 0.004142 | 0.004037 | 0.004409 | 0.001706 | -0.005934 | -0.000851 | -0.009962 | 0.005672 | 0.000903 | 0.001402 | -0.009675 | -0.000516 | 0.001880 | 0.003200 | 0.006271 | -0.010285 | 0.014949 | 0.009111 | 0.003172 | -0.001889 | 0.007462 | -0.000949 | -0.001124 | -0.003608 | -0.002223 | 0.000426 | 0.009530 | 0.003036 | -0.002150 | 0.001342 | -0.004454 | 0.001279 | -0.006633 | -0.004937 | 0.006651 | -0.000652 | -0.002427 | 0.001391 |
| HHN6 | 0.112969 | 0.469697 | -0.674756 | -0.467398 | 0.081799 | -0.224749 | -0.052986 | 0.012937 | -0.095381 | -0.036250 | 0.052951 | -0.007296 | -0.068190 | 0.007077 | -0.021160 | 0.002965 | -0.003478 | -0.016731 | 0.034801 | 0.011077 | 0.011011 | 0.023960 | -0.002040 | -0.022869 | 0.005683 | -0.002194 | 0.043384 | -0.031418 | 0.031467 | -0.025974 | -0.002755 | 0.005603 | -0.026413 | -0.022516 | 0.004525 | -0.003091 | -0.007272 | -0.002397 | 0.011931 | 0.005128 | 0.006408 | 0.003151 | -0.011028 | -0.001509 | -0.010002 | 0.006989 | 0.000198 | 0.002702 | -0.014870 | -0.002835 | 0.002146 | 0.004893 | 0.006751 | -0.015317 | 0.024326 | 0.014364 | 0.005762 | -0.002388 | 0.008173 | -0.002993 | 0.001103 | -0.005598 | -0.000844 | 0.000907 | 0.015753 | 0.002108 | -0.000513 | 0.000489 | -0.005645 | 0.002629 | -0.011011 | -0.007204 | 0.009272 | -0.001051 | -0.002834 | 0.006171 |
| MARR1 | -0.632954 | 0.645670 | 0.371827 | 0.140451 | 0.004948 | -0.125661 | -0.017510 | 0.003475 | -0.038242 | -0.031007 | -0.017461 | -0.013869 | 0.002387 | 0.048814 | -0.005944 | -0.011013 | 0.012170 | -0.010802 | -0.036991 | 0.010181 | 0.003378 | 0.006217 | -0.010303 | -0.006594 | 0.002423 | -0.005423 | 0.007081 | 0.000746 | -0.000808 | 0.009063 | -0.003778 | -0.007616 | -0.000519 | 0.001006 | 0.002252 | 0.003637 | -0.000615 | 0.000267 | -0.003026 | 0.000218 | -0.004094 | -0.005125 | 0.002143 | 0.004118 | 0.002385 | -0.001054 | 0.001881 | 0.005941 | 0.005660 | 0.003451 | 0.001121 | -0.000288 | -0.002748 | -0.000155 | -0.004253 | -0.007301 | -0.001747 | -0.000047 | -0.004886 | -0.000101 | 0.001403 | 0.002533 | 0.001279 | -0.002888 | -0.003540 | 0.001264 | 0.000678 | -0.001781 | -0.000503 | 0.001906 | -0.000380 | -0.000116 | 0.000151 | -0.000158 | -0.001949 | -0.001258 |
| MARR2 | 0.641968 | -0.533795 | -0.397163 | 0.164855 | 0.219900 | -0.072693 | 0.050612 | -0.125245 | 0.030193 | 0.055244 | -0.126947 | 0.078791 | 0.022216 | -0.074498 | 0.032820 | -0.052644 | 0.006207 | 0.043980 | 0.014416 | -0.025490 | -0.001667 | -0.008831 | 0.022597 | 0.009292 | -0.018081 | 0.011261 | -0.026332 | 0.011929 | 0.015895 | -0.014232 | 0.015750 | 0.018802 | 0.016427 | 0.016247 | 0.007862 | 0.005033 | 0.016900 | -0.011395 | -0.001161 | 0.002522 | -0.001053 | 0.007399 | -0.002895 | -0.006601 | 0.006492 | -0.000746 | -0.005602 | -0.010942 | -0.008815 | -0.006316 | -0.012986 | -0.002891 | -0.009529 | 0.006745 | -0.005731 | 0.005720 | 0.004170 | 0.001057 | -0.001736 | -0.002250 | -0.000951 | -0.000480 | 0.007471 | -0.000336 | 0.002428 | -0.002598 | 0.003779 | -0.002847 | 0.004606 | -0.008533 | 0.007613 | -0.003926 | -0.004089 | 0.003034 | -0.004467 | 0.000351 |
| MARR3 | 0.727226 | -0.310758 | 0.530751 | -0.088100 | 0.219910 | -0.043238 | 0.024125 | 0.011418 | 0.016240 | -0.070680 | 0.043984 | -0.114561 | 0.042808 | -0.014980 | -0.041518 | 0.002135 | 0.011194 | 0.063289 | 0.039905 | -0.034194 | 0.002102 | -0.012127 | 0.018852 | 0.018187 | -0.011749 | 0.001497 | -0.014877 | -0.006105 | 0.003266 | -0.012689 | -0.010079 | -0.000041 | 0.001667 | -0.001344 | -0.001970 | 0.001488 | -0.003581 | 0.007586 | -0.001078 | -0.002533 | 0.012368 | 0.008098 | -0.006551 | -0.004198 | -0.011154 | 0.004628 | -0.001576 | -0.005797 | -0.008322 | -0.000820 | 0.004581 | 0.005537 | 0.004139 | -0.001089 | 0.000863 | 0.002746 | 0.004327 | -0.002969 | 0.007080 | 0.006809 | -0.003694 | 0.003572 | -0.004311 | 0.000911 | -0.002205 | -0.003995 | -0.001893 | 0.002902 | 0.005684 | 0.001841 | -0.003116 | 0.000340 | 0.000831 | 0.000935 | -0.002003 | 0.000240 |
| MARR4 | 0.222474 | -0.535977 | -0.712203 | -0.098404 | 0.247873 | 0.125248 | -0.088138 | -0.179088 | 0.023299 | 0.087683 | 0.069222 | 0.035211 | -0.042043 | -0.039355 | 0.012600 | 0.069401 | -0.025180 | -0.046729 | 0.022294 | 0.027932 | -0.011099 | -0.002768 | -0.006400 | 0.004497 | 0.000821 | 0.002659 | 0.010998 | 0.000175 | 0.000479 | 0.004874 | 0.003040 | 0.009980 | -0.013547 | -0.005291 | -0.004972 | -0.014880 | -0.003539 | 0.001309 | 0.009666 | 0.005133 | -0.002501 | -0.001129 | 0.002965 | -0.002916 | 0.000878 | -0.000494 | 0.001684 | -0.001630 | 0.001206 | -0.000639 | 0.001819 | -0.002201 | 0.009848 | -0.001429 | 0.008958 | 0.007189 | -0.001016 | 0.001403 | 0.005173 | -0.002770 | 0.001108 | -0.006806 | -0.003891 | 0.004946 | 0.007497 | 0.000236 | -0.005320 | 0.002155 | -0.006195 | -0.001861 | -0.000877 | 0.002946 | 0.001624 | -0.002903 | 0.006919 | 0.000279 |
| HHP1 | -0.515153 | 0.709794 | -0.417667 | -0.151193 | 0.100439 | -0.126189 | 0.015140 | -0.009790 | -0.028993 | -0.040022 | 0.032135 | -0.007548 | -0.013731 | 0.011481 | -0.021857 | 0.019362 | -0.014803 | -0.017028 | 0.012796 | 0.008848 | -0.003622 | 0.004721 | 0.013096 | -0.003586 | 0.002834 | 0.003555 | 0.012063 | -0.012044 | 0.010792 | -0.008969 | 0.002255 | -0.004027 | -0.006526 | -0.005411 | -0.004409 | 0.003020 | -0.001914 | 0.006675 | -0.001567 | -0.000679 | -0.005666 | -0.006069 | -0.001443 | 0.006312 | -0.005241 | 0.001627 | 0.006754 | 0.007427 | 0.000920 | 0.001106 | 0.005302 | -0.000177 | 0.003258 | -0.004118 | 0.005664 | 0.000492 | -0.001994 | -0.001095 | 0.001575 | 0.000515 | -0.000704 | -0.000220 | -0.001835 | -0.000296 | 0.000937 | 0.001916 | -0.003314 | 0.001096 | -0.000977 | 0.000761 | -0.003872 | -0.000611 | 0.004015 | -0.002431 | -0.004648 | -0.001288 |
| HHP2 | -0.447437 | 0.749293 | -0.397683 | -0.159378 | 0.169286 | -0.135681 | -0.014255 | -0.044884 | -0.040395 | -0.026672 | 0.023943 | -0.009448 | -0.016771 | 0.012516 | -0.014655 | 0.017573 | -0.015195 | -0.015662 | 0.010171 | 0.009212 | -0.002623 | 0.006172 | 0.007716 | -0.006184 | 0.000025 | 0.005260 | 0.008777 | -0.008211 | 0.010089 | -0.005585 | -0.002070 | -0.004660 | -0.003220 | -0.006106 | -0.001564 | 0.001520 | -0.001047 | 0.004788 | -0.000623 | 0.000001 | -0.003222 | -0.002598 | -0.001725 | 0.003863 | -0.003321 | 0.001094 | 0.003192 | 0.004860 | -0.000268 | 0.001579 | 0.002984 | -0.000234 | 0.002442 | -0.003397 | 0.004681 | 0.002017 | -0.000279 | -0.000409 | 0.000910 | 0.000254 | -0.000996 | -0.001349 | -0.002221 | -0.001219 | 0.002401 | 0.001313 | -0.002126 | -0.000687 | -0.001123 | 0.001029 | -0.002762 | -0.001194 | 0.003390 | -0.001333 | -0.002011 | -0.000425 |
| DW1 | -0.605865 | 0.703631 | 0.197693 | -0.174374 | 0.183278 | 0.070105 | 0.034544 | 0.076358 | -0.076077 | -0.000706 | -0.051698 | -0.018422 | 0.012442 | -0.016385 | 0.025733 | 0.011150 | 0.032949 | -0.035323 | 0.035066 | -0.014287 | -0.028649 | -0.017871 | -0.008429 | 0.054033 | -0.015862 | -0.014748 | 0.025074 | 0.030014 | 0.009118 | 0.026888 | 0.017401 | 0.002600 | 0.010453 | -0.004786 | -0.012913 | -0.000964 | 0.005854 | 0.004966 | 0.012584 | 0.009491 | 0.006101 | 0.006705 | -0.002125 | 0.005426 | 0.002321 | -0.001567 | -0.007318 | -0.001836 | 0.003489 | 0.000073 | 0.000532 | 0.005695 | -0.010158 | -0.002275 | -0.001037 | -0.001275 | 0.007685 | 0.002157 | 0.003650 | -0.005246 | -0.005223 | -0.000144 | 0.002594 | 0.006659 | 0.000637 | -0.002051 | 0.001935 | 0.002487 | -0.000029 | 0.003181 | -0.000409 | 0.002078 | -0.005099 | 0.000193 | 0.001520 | -0.002284 |
| DW2 | -0.513509 | 0.770806 | 0.218356 | -0.169360 | 0.175324 | 0.096555 | 0.017999 | 0.071540 | -0.070869 | 0.001070 | -0.052351 | -0.013737 | 0.011252 | -0.015880 | 0.022358 | 0.020603 | 0.028258 | -0.024467 | 0.029373 | -0.017408 | -0.035373 | -0.012189 | -0.002864 | 0.044839 | -0.025598 | -0.016285 | 0.022823 | 0.024343 | 0.002761 | 0.031262 | 0.003817 | -0.014987 | 0.007357 | -0.022339 | -0.010085 | -0.001539 | 0.001579 | 0.002920 | 0.014606 | 0.003788 | -0.000707 | 0.001907 | 0.004194 | 0.001987 | -0.002084 | 0.001815 | -0.001336 | 0.001281 | 0.001678 | 0.000460 | 0.001528 | 0.005879 | -0.005927 | -0.000780 | -0.001807 | -0.005451 | 0.006482 | 0.001986 | 0.000118 | -0.002107 | -0.000320 | 0.002666 | 0.001163 | 0.005107 | 0.002046 | -0.003739 | 0.001838 | 0.003170 | -0.000714 | 0.000977 | 0.000385 | 0.001768 | -0.001985 | -0.000744 | 0.004172 | -0.001974 |
| DW3 | 0.666380 | -0.366816 | -0.291410 | -0.106276 | 0.328877 | 0.218575 | -0.027075 | 0.003425 | -0.002424 | -0.077487 | -0.128601 | 0.003802 | -0.039002 | 0.077012 | 0.002402 | 0.070217 | -0.161165 | -0.120556 | -0.102386 | -0.151937 | 0.139198 | 0.046284 | -0.010070 | 0.032822 | 0.075463 | 0.088571 | -0.046631 | 0.006175 | 0.009204 | -0.035946 | -0.029245 | 0.055993 | -0.044945 | 0.042322 | 0.000122 | 0.009114 | -0.034463 | 0.014710 | -0.001480 | -0.008833 | 0.019621 | -0.017785 | 0.009960 | 0.006372 | -0.003654 | 0.003492 | -0.003334 | 0.000434 | -0.006225 | 0.020463 | -0.008136 | 0.007410 | 0.001414 | -0.009771 | -0.011675 | -0.019703 | -0.000610 | -0.011745 | 0.008756 | 0.008726 | 0.007510 | 0.006779 | 0.002157 | 0.001512 | 0.002413 | 0.003771 | -0.001640 | -0.013503 | -0.015455 | 0.007176 | -0.021707 | -0.004505 | 0.003890 | -0.006551 | -0.005305 | -0.005316 |
| DW4 | 0.328762 | -0.869391 | -0.275062 | 0.155007 | 0.090160 | -0.005021 | -0.042729 | -0.082824 | 0.043473 | -0.024341 | 0.067777 | 0.012870 | -0.029594 | 0.041523 | -0.032849 | -0.041945 | -0.048354 | 0.026901 | -0.015991 | 0.002253 | 0.024441 | 0.019261 | -0.011872 | -0.007455 | 0.002779 | 0.022126 | 0.015178 | 0.008441 | 0.001673 | -0.000343 | -0.015924 | -0.012086 | -0.001482 | -0.015226 | -0.000900 | 0.009987 | -0.005408 | 0.007843 | -0.003397 | -0.006058 | -0.002174 | -0.007556 | -0.000865 | 0.005893 | 0.000392 | 0.000470 | 0.001336 | 0.005890 | 0.001992 | 0.007507 | 0.001363 | -0.002628 | -0.004370 | -0.004655 | -0.002810 | -0.004924 | -0.003854 | 0.004875 | -0.005052 | 0.002108 | -0.003364 | 0.001931 | -0.003714 | -0.000358 | -0.002928 | 0.003595 | 0.000958 | -0.004274 | -0.004958 | 0.001938 | -0.001891 | 0.000604 | 0.005418 | 0.002806 | 0.001475 | 0.002193 |
| DW5 | 0.262144 | -0.890769 | -0.256711 | 0.183316 | 0.050894 | -0.036488 | -0.042457 | -0.090307 | 0.047267 | -0.015473 | 0.091775 | 0.013339 | -0.026585 | 0.034076 | -0.035965 | -0.055513 | -0.029509 | 0.046326 | -0.002796 | 0.024053 | 0.006720 | 0.014288 | -0.011403 | -0.012754 | -0.007776 | 0.011367 | 0.023083 | 0.008265 | 0.000532 | 0.004742 | -0.013138 | -0.021103 | 0.004777 | -0.022525 | -0.000969 | 0.009564 | -0.000962 | 0.006403 | -0.003471 | -0.005310 | -0.005171 | -0.005657 | -0.002370 | 0.005492 | 0.000919 | 0.000044 | 0.001917 | 0.006319 | 0.003091 | 0.005203 | 0.002638 | -0.003887 | -0.004974 | -0.003652 | -0.001411 | -0.002518 | -0.004052 | 0.006943 | -0.006734 | 0.001031 | -0.004716 | 0.001114 | -0.004338 | -0.000587 | -0.003503 | 0.003386 | 0.001282 | -0.002740 | -0.003199 | 0.001097 | 0.001047 | 0.001277 | 0.005302 | 0.003959 | 0.002322 | 0.003110 |
| DW6 | 0.214966 | -0.903502 | -0.223763 | 0.197687 | 0.026820 | -0.051025 | -0.046066 | -0.091391 | 0.060623 | -0.006766 | 0.111278 | 0.011197 | -0.029648 | 0.032108 | -0.039249 | -0.062477 | -0.013982 | 0.061993 | 0.007843 | 0.041008 | -0.012378 | 0.008868 | -0.007601 | -0.016972 | -0.021701 | -0.001591 | 0.031307 | 0.008008 | -0.001717 | 0.013422 | -0.009125 | -0.029255 | 0.006565 | -0.031618 | -0.001021 | 0.006550 | 0.003313 | 0.004032 | -0.003394 | -0.001998 | -0.007229 | -0.002267 | 0.000200 | 0.002271 | -0.000189 | -0.000581 | 0.003585 | 0.007492 | 0.003570 | 0.002297 | 0.003608 | -0.004987 | -0.004777 | -0.001526 | -0.000885 | -0.001407 | -0.003527 | 0.006519 | -0.007871 | 0.001508 | -0.003833 | -0.000018 | -0.003374 | -0.001673 | -0.002389 | 0.002625 | 0.000468 | -0.001455 | -0.001211 | 0.001038 | 0.003540 | 0.000419 | 0.004981 | 0.002349 | 0.003172 | 0.003224 |
| DW7 | 0.547985 | -0.374933 | 0.174022 | -0.012848 | -0.001082 | 0.150273 | -0.017706 | -0.098780 | -0.169412 | -0.098300 | 0.285905 | -0.213671 | 0.086986 | -0.160725 | -0.066242 | 0.358334 | -0.096391 | -0.008564 | 0.267854 | -0.096811 | -0.086506 | -0.049832 | 0.000736 | -0.096186 | -0.044619 | 0.098246 | -0.060374 | 0.064907 | 0.120311 | -0.037071 | -0.020702 | -0.002954 | 0.076185 | 0.019287 | -0.008263 | -0.018866 | 0.021320 | 0.028918 | -0.014428 | -0.011580 | -0.030896 | 0.015461 | 0.016074 | 0.000652 | 0.015693 | -0.046036 | -0.011020 | 0.008544 | 0.007467 | 0.008267 | -0.024812 | -0.013153 | -0.016491 | -0.003011 | -0.033339 | -0.006824 | -0.004401 | 0.011917 | -0.011404 | 0.006474 | -0.003893 | -0.001796 | 0.002877 | -0.003301 | -0.009729 | 0.001025 | 0.011984 | 0.000526 | -0.001169 | -0.000488 | 0.004157 | 0.014403 | -0.000169 | 0.010493 | -0.002771 | -0.002541 |
| DW8 | 0.542251 | -0.311175 | 0.305828 | -0.016644 | 0.065445 | 0.068228 | 0.017494 | -0.029489 | -0.089547 | -0.151239 | 0.236612 | -0.269570 | 0.101556 | -0.157838 | -0.107947 | 0.186837 | -0.070190 | 0.105353 | 0.266159 | -0.163961 | -0.044329 | -0.027908 | 0.053791 | -0.077011 | -0.053053 | 0.104957 | -0.113632 | 0.115528 | 0.186337 | -0.061677 | -0.054823 | 0.002229 | 0.121333 | -0.006586 | -0.067680 | -0.112138 | 0.005969 | 0.066592 | -0.012555 | -0.009347 | -0.073124 | 0.021153 | 0.016816 | 0.034407 | -0.013141 | -0.001413 | 0.002476 | 0.004356 | 0.049046 | 0.018584 | -0.017670 | -0.009733 | 0.008975 | 0.011805 | -0.019886 | 0.023283 | 0.020455 | 0.002305 | -0.007282 | 0.005331 | 0.002185 | -0.013413 | 0.003719 | -0.010009 | 0.001605 | 0.005190 | -0.005916 | 0.010585 | -0.011083 | -0.004450 | 0.006790 | 0.023731 | -0.013126 | 0.002189 | 0.011023 | 0.009581 |
| DW9 | 0.339956 | -0.340748 | -0.118362 | -0.002249 | -0.112195 | 0.233303 | -0.071651 | -0.176921 | -0.240676 | 0.030034 | 0.258353 | -0.035203 | 0.027101 | -0.106103 | 0.024596 | 0.513206 | -0.103319 | -0.200965 | 0.167994 | 0.055472 | -0.125169 | -0.067583 | -0.090440 | -0.092472 | -0.012453 | 0.049231 | 0.054164 | -0.046469 | -0.039279 | 0.019086 | 0.045677 | -0.010866 | -0.029962 | 0.056264 | 0.096778 | 0.148243 | 0.039548 | -0.046615 | -0.012504 | -0.010844 | 0.053038 | -0.000087 | 0.008697 | -0.057342 | 0.059169 | -0.104713 | -0.030091 | 0.012644 | -0.066619 | -0.012603 | -0.027476 | -0.014048 | -0.053749 | -0.027048 | -0.043559 | -0.055943 | -0.044938 | 0.023676 | -0.014037 | 0.006071 | -0.012679 | 0.018645 | 0.000276 | 0.009131 | -0.025720 | -0.006538 | 0.038096 | -0.016978 | 0.016294 | 0.006677 | -0.001997 | -0.006888 | 0.021947 | 0.020651 | -0.025262 | -0.022304 |
| HV1 | -0.763820 | -0.548202 | 0.027541 | -0.260120 | -0.069105 | -0.088212 | -0.106835 | -0.083194 | 0.006987 | 0.045505 | -0.062211 | 0.008961 | 0.062130 | -0.010083 | 0.014627 | 0.014956 | -0.002471 | 0.025674 | 0.025256 | -0.006712 | 0.027113 | -0.010373 | 0.023632 | -0.019534 | 0.020681 | -0.000377 | -0.000648 | -0.003277 | -0.015704 | 0.017154 | -0.011264 | -0.009066 | -0.006861 | 0.002165 | 0.000081 | 0.010816 | 0.002316 | 0.014008 | 0.013427 | 0.003600 | -0.007615 | -0.003703 | 0.005799 | 0.007626 | -0.003385 | -0.004321 | 0.007446 | 0.010936 | 0.000373 | 0.002843 | 0.003457 | -0.004442 | 0.007194 | 0.002631 | -0.002927 | -0.003149 | -0.004547 | 0.000995 | 0.002487 | 0.003744 | 0.000205 | -0.002152 | -0.008402 | 0.000447 | -0.001936 | 0.004289 | -0.002142 | 0.006826 | 0.000474 | 0.002573 | 0.004129 | -0.000537 | 0.002289 | 0.001519 | 0.001053 | -0.002369 |
| HV2 | -0.767168 | -0.547527 | 0.043093 | -0.248463 | -0.078828 | -0.091714 | -0.102116 | -0.090586 | 0.004738 | 0.042648 | -0.059536 | 0.007541 | 0.057206 | -0.010147 | 0.017766 | 0.013855 | -0.003748 | 0.022893 | 0.024768 | -0.008348 | 0.027413 | -0.008163 | 0.021901 | -0.017113 | 0.016792 | 0.001374 | 0.001186 | -0.004037 | -0.015553 | 0.014776 | -0.011072 | -0.009909 | -0.006282 | 0.001869 | 0.001479 | 0.009329 | 0.002606 | 0.013121 | 0.014121 | 0.003973 | -0.007020 | -0.003475 | 0.004957 | 0.007540 | -0.003061 | -0.004491 | 0.006602 | 0.009458 | -0.000421 | 0.002893 | 0.002970 | -0.004308 | 0.006663 | 0.003092 | -0.002244 | -0.002989 | -0.004459 | 0.000774 | 0.001432 | 0.002996 | -0.000374 | -0.001808 | -0.008101 | 0.000600 | -0.001411 | 0.003483 | -0.001745 | 0.006102 | 0.000349 | 0.002486 | 0.003531 | -0.000363 | 0.002239 | 0.001259 | 0.000272 | -0.001371 |
| HV3 | -0.883169 | -0.415091 | -0.054868 | -0.135554 | 0.029042 | -0.127884 | -0.005461 | 0.035653 | -0.009180 | 0.014613 | -0.038423 | 0.000541 | 0.022373 | -0.023676 | 0.003126 | 0.005509 | -0.013316 | -0.003165 | 0.036039 | 0.010519 | 0.005668 | -0.011516 | 0.004347 | 0.012701 | 0.010461 | -0.009590 | 0.000028 | 0.000340 | 0.004005 | -0.003318 | 0.018369 | -0.000963 | 0.004641 | 0.004912 | -0.000244 | 0.002510 | 0.000984 | 0.005734 | -0.011971 | 0.000962 | -0.000715 | 0.000452 | 0.001614 | 0.003795 | -0.003246 | 0.002437 | 0.008576 | 0.008926 | 0.004328 | -0.000950 | 0.005945 | -0.003883 | 0.002206 | 0.000996 | 0.001737 | 0.000678 | -0.006766 | -0.003012 | 0.004052 | -0.000702 | 0.004454 | -0.001686 | -0.005342 | -0.002363 | -0.001952 | -0.000890 | -0.009162 | 0.002743 | 0.005011 | -0.002654 | 0.003348 | -0.009173 | 0.003092 | -0.007643 | 0.002559 | -0.001089 |
| HV4 | -0.818731 | -0.526713 | -0.112066 | -0.099207 | 0.056471 | -0.128359 | 0.008964 | 0.050241 | -0.016021 | 0.008431 | -0.028259 | -0.001867 | 0.024925 | -0.031536 | 0.008881 | -0.004177 | -0.016541 | -0.001815 | 0.030787 | 0.008314 | 0.008284 | -0.010148 | 0.002250 | 0.014870 | 0.009957 | -0.012974 | -0.001318 | -0.002752 | 0.006400 | -0.006877 | 0.019469 | -0.001161 | 0.006021 | 0.005511 | 0.002943 | 0.002994 | -0.000786 | 0.007700 | -0.012470 | 0.001921 | -0.001269 | 0.001030 | 0.003368 | 0.004033 | -0.003226 | 0.002760 | 0.010398 | 0.008540 | 0.003401 | -0.001354 | 0.004847 | -0.005165 | 0.003165 | 0.003281 | 0.001846 | 0.000379 | -0.007573 | -0.002533 | 0.002844 | -0.000714 | 0.005196 | -0.002117 | -0.006054 | -0.001492 | -0.001430 | -0.002092 | -0.009512 | 0.003386 | 0.004388 | -0.003909 | 0.002117 | -0.008096 | 0.003361 | -0.008182 | 0.002612 | 0.000082 |
| HU1 | -0.577629 | 0.678951 | 0.429189 | -0.055677 | 0.054326 | -0.057538 | 0.041933 | 0.040710 | 0.033790 | 0.007444 | -0.013666 | -0.022758 | -0.008375 | -0.006847 | 0.015600 | 0.034703 | 0.023811 | -0.029197 | -0.000913 | 0.016262 | -0.014375 | -0.018350 | 0.016460 | -0.006290 | -0.004287 | -0.016453 | -0.007144 | -0.004366 | -0.000934 | 0.001436 | 0.017445 | 0.017719 | -0.008394 | 0.016088 | -0.004271 | -0.004133 | 0.005386 | 0.000393 | -0.006124 | 0.007748 | -0.000138 | 0.002693 | -0.002388 | -0.003765 | 0.000802 | -0.002369 | 0.000444 | -0.001716 | -0.000823 | 0.002065 | 0.000738 | -0.003732 | 0.005855 | -0.000191 | -0.001190 | 0.002993 | -0.000154 | 0.001172 | 0.004723 | 0.005028 | -0.000310 | -0.003941 | 0.002400 | 0.005918 | -0.001593 | 0.003400 | -0.002924 | 0.001729 | -0.001757 | 0.002468 | -0.000976 | 0.002500 | 0.003966 | -0.003049 | -0.001495 | -0.001010 |
| HU2 | 0.564467 | -0.664239 | -0.426176 | 0.128184 | 0.113270 | 0.001932 | -0.072115 | -0.122004 | -0.044377 | -0.003387 | 0.013346 | 0.017670 | 0.009452 | 0.008817 | -0.019237 | -0.030354 | -0.023040 | 0.030199 | -0.004224 | -0.013458 | 0.014175 | 0.018731 | -0.018503 | 0.009642 | 0.000756 | 0.017623 | 0.008125 | 0.006101 | 0.004287 | 0.000679 | -0.019550 | -0.017373 | 0.007478 | -0.015949 | 0.005396 | 0.002992 | -0.005131 | -0.000183 | 0.007505 | -0.006609 | -0.000891 | -0.003511 | 0.003003 | 0.003667 | -0.000193 | 0.002528 | -0.000099 | 0.001976 | 0.001634 | -0.001571 | -0.000849 | 0.003783 | -0.005629 | 0.000605 | 0.000748 | -0.003945 | 0.000350 | -0.001255 | -0.005290 | -0.005434 | 0.000636 | 0.004280 | -0.002674 | -0.006467 | 0.001980 | -0.004071 | 0.002148 | -0.002205 | 0.001522 | -0.003207 | 0.001242 | -0.002423 | -0.004174 | 0.002952 | 0.001493 | 0.000551 |
| HU3 | -0.609329 | 0.179715 | -0.230877 | 0.047749 | 0.689538 | 0.037278 | -0.073603 | -0.014474 | 0.004849 | -0.023434 | 0.062916 | -0.025032 | 0.086333 | -0.016509 | -0.007199 | 0.038319 | 0.062463 | 0.077983 | -0.007354 | 0.001236 | -0.006085 | 0.058257 | 0.004880 | -0.006372 | 0.038795 | 0.041228 | -0.068461 | -0.083135 | -0.034208 | 0.071593 | 0.025831 | 0.004545 | 0.027021 | -0.009766 | -0.021051 | -0.013086 | -0.004996 | -0.006397 | -0.011750 | -0.000285 | 0.006548 | -0.017390 | 0.004078 | 0.008618 | 0.029767 | 0.013761 | -0.019743 | -0.025134 | 0.003703 | -0.002406 | -0.015378 | -0.001164 | -0.022669 | -0.003774 | 0.008444 | 0.020575 | -0.002059 | 0.002661 | 0.008721 | -0.015220 | -0.003602 | -0.010135 | 0.003116 | 0.014916 | 0.005555 | 0.003968 | 0.007986 | -0.001178 | -0.008968 | -0.010542 | 0.002965 | -0.005508 | -0.004165 | 0.011849 | 0.014634 | -0.001081 |
| HU4 | 0.628241 | -0.001031 | 0.452224 | 0.169937 | -0.354291 | -0.260668 | 0.008975 | -0.250515 | -0.033701 | 0.048412 | -0.091791 | 0.010183 | -0.117535 | 0.027633 | 0.001837 | -0.027852 | -0.076345 | -0.112340 | -0.007895 | 0.012442 | 0.003513 | -0.084217 | -0.009031 | 0.018526 | -0.066790 | -0.057486 | 0.095700 | 0.119366 | 0.058457 | -0.090840 | -0.037863 | -0.000001 | -0.042870 | 0.018571 | 0.031724 | 0.012904 | 0.009334 | 0.009668 | 0.019232 | 0.006580 | -0.012572 | 0.021885 | -0.004183 | -0.013288 | -0.038638 | -0.019044 | 0.028496 | 0.034939 | -0.002515 | 0.005595 | 0.021013 | 0.000725 | 0.033661 | 0.006545 | -0.013479 | -0.030802 | 0.003488 | -0.003605 | -0.012592 | 0.021012 | 0.005987 | 0.014037 | -0.004521 | -0.020694 | -0.006813 | -0.006785 | -0.014525 | 0.000494 | 0.011052 | 0.012662 | -0.003456 | 0.008550 | 0.006156 | -0.017552 | -0.020631 | -0.000405 |
| HU5 | 0.239781 | 0.159283 | 0.749442 | 0.153006 | -0.361022 | -0.280458 | -0.064303 | -0.126151 | 0.008891 | 0.093931 | -0.025367 | 0.009609 | -0.118556 | 0.031660 | 0.034655 | -0.004074 | -0.106601 | -0.123397 | 0.024452 | 0.022534 | 0.041893 | -0.007593 | 0.060986 | 0.023604 | -0.049555 | -0.043350 | 0.090594 | 0.066860 | 0.024527 | -0.083556 | -0.002627 | -0.007014 | -0.028180 | 0.037971 | 0.017198 | 0.015321 | 0.015443 | 0.010394 | 0.002731 | 0.007061 | -0.015996 | 0.012500 | -0.010574 | -0.000582 | -0.034613 | -0.027642 | 0.021310 | 0.022868 | 0.001583 | 0.001003 | 0.026094 | 0.009880 | 0.018366 | 0.012474 | -0.001587 | -0.025032 | 0.007500 | -0.008699 | -0.001355 | -0.000257 | 0.006130 | 0.004187 | 0.005545 | -0.004106 | 0.007455 | -0.007953 | -0.010263 | 0.001936 | 0.018975 | 0.013125 | -0.001939 | 0.006518 | -0.008394 | -0.019492 | -0.008891 | -0.002731 |
| HHD1 | -0.345202 | 0.762211 | -0.527994 | -0.058796 | 0.066868 | -0.036268 | 0.037256 | -0.039711 | -0.031298 | -0.064678 | 0.003007 | -0.032746 | 0.003574 | 0.015733 | -0.021712 | -0.008304 | -0.018865 | 0.011181 | 0.005991 | -0.001727 | -0.008075 | -0.000718 | 0.018699 | -0.006184 | 0.002698 | 0.005438 | 0.001898 | -0.005711 | 0.007443 | -0.006005 | -0.001428 | -0.006737 | 0.002851 | -0.000680 | -0.000993 | 0.009219 | 0.005287 | 0.006251 | -0.002561 | -0.002018 | -0.005755 | -0.004997 | -0.000222 | 0.003777 | 0.000454 | -0.001223 | 0.004782 | 0.004734 | -0.001979 | -0.000700 | 0.002200 | -0.000785 | -0.001169 | -0.000123 | -0.002162 | -0.003579 | -0.000393 | 0.000009 | -0.000826 | 0.002346 | -0.003703 | 0.002001 | -0.003001 | -0.001717 | -0.002449 | 0.001729 | -0.000576 | 0.000003 | 0.003622 | -0.000720 | -0.000301 | -0.000850 | 0.002359 | -0.000769 | -0.003733 | -0.002115 |
| HHD2 | -0.542468 | 0.815939 | -0.001576 | -0.078950 | 0.105370 | -0.127977 | 0.048433 | -0.014236 | -0.015927 | -0.019225 | 0.007205 | 0.005637 | -0.000837 | 0.022772 | -0.004407 | 0.014900 | -0.006172 | -0.025693 | -0.001171 | 0.011745 | 0.001464 | 0.007816 | -0.002716 | -0.009620 | 0.002751 | 0.011739 | -0.001898 | 0.002562 | 0.009173 | 0.001840 | 0.000194 | -0.010598 | 0.008670 | 0.001695 | -0.004041 | 0.005898 | 0.002841 | 0.006074 | -0.001371 | -0.004123 | -0.008257 | -0.007061 | 0.001037 | 0.006750 | 0.005291 | -0.002434 | 0.001786 | 0.007679 | 0.005527 | 0.003149 | 0.001858 | -0.002362 | -0.002552 | 0.000915 | -0.002475 | -0.004168 | -0.002391 | 0.000999 | -0.005689 | 0.000634 | -0.002325 | 0.001531 | -0.001248 | -0.003234 | -0.004588 | 0.000415 | 0.000754 | -0.002592 | 0.002073 | 0.000909 | 0.000708 | 0.001537 | 0.000903 | 0.001388 | -0.001826 | -0.000844 |
| HHD3 | -0.685852 | 0.687669 | 0.207813 | 0.016256 | -0.008252 | -0.089896 | -0.010589 | 0.016475 | -0.029312 | -0.023313 | 0.025681 | -0.007221 | 0.001524 | 0.026434 | -0.012323 | 0.022835 | -0.003953 | -0.016061 | -0.009179 | 0.005369 | -0.005022 | 0.003926 | -0.008569 | -0.009218 | 0.000025 | 0.001959 | 0.002018 | 0.001297 | 0.003117 | 0.005527 | -0.003994 | -0.007939 | 0.002927 | -0.003426 | -0.002482 | 0.001730 | -0.000528 | 0.003596 | -0.003169 | -0.000256 | -0.005435 | -0.005561 | 0.002053 | 0.005356 | 0.001206 | -0.000585 | 0.002142 | 0.006326 | 0.005647 | 0.004547 | 0.001688 | -0.000328 | -0.001819 | -0.001383 | -0.002905 | -0.005349 | -0.001921 | 0.000572 | -0.003322 | 0.000252 | 0.000138 | 0.001937 | 0.000383 | -0.002425 | -0.002445 | 0.001423 | -0.000159 | -0.001778 | -0.002066 | 0.002384 | -0.001425 | 0.001104 | 0.001602 | -0.000462 | -0.001598 | -0.001095 |
| HHD4 | -0.594741 | 0.735672 | -0.305046 | 0.003822 | -0.010970 | -0.020430 | -0.025493 | 0.004157 | -0.033726 | -0.062444 | 0.028296 | -0.043466 | 0.004802 | 0.023709 | -0.028496 | 0.009776 | -0.009327 | 0.014340 | -0.003791 | -0.007830 | -0.014008 | -0.007588 | 0.010831 | -0.002886 | 0.000021 | -0.004184 | 0.003927 | -0.006887 | 0.001890 | -0.000549 | -0.006936 | -0.004320 | -0.002739 | -0.005845 | 0.000912 | 0.003761 | 0.001797 | 0.004861 | -0.004361 | 0.002618 | -0.002816 | -0.003745 | -0.000456 | 0.002673 | -0.002726 | 0.000215 | 0.005129 | 0.003826 | -0.001516 | 0.002660 | 0.001386 | 0.000696 | -0.000126 | -0.002357 | -0.002849 | -0.004619 | -0.000353 | -0.000842 | 0.001187 | 0.001857 | -0.000767 | 0.002209 | -0.001187 | -0.000776 | -0.000882 | 0.001958 | -0.002741 | 0.000367 | -0.002099 | 0.001191 | -0.003551 | -0.000274 | 0.003316 | -0.003033 | -0.003429 | -0.002699 |
| HHD5 | -0.475685 | 0.835930 | 0.050867 | -0.032737 | 0.200062 | -0.139653 | 0.040774 | -0.036565 | 0.007461 | -0.016993 | -0.026166 | 0.015088 | -0.004588 | 0.049489 | 0.003164 | -0.036997 | 0.009060 | -0.014065 | -0.042034 | 0.022777 | 0.013415 | 0.007536 | -0.004656 | 0.003947 | 0.004966 | -0.000386 | 0.003044 | -0.000750 | -0.005120 | 0.005036 | -0.001378 | -0.008150 | -0.001740 | 0.001471 | 0.001901 | 0.009271 | 0.001833 | 0.000291 | 0.002533 | -0.001748 | -0.001707 | -0.006732 | -0.002407 | 0.002696 | 0.005697 | 0.001156 | 0.001115 | 0.003705 | 0.001743 | 0.002628 | 0.002003 | -0.001380 | -0.000406 | 0.003070 | -0.000539 | -0.004275 | -0.000808 | -0.001188 | -0.004799 | -0.000053 | -0.002516 | 0.002770 | -0.002165 | -0.002483 | -0.004471 | -0.001412 | -0.000866 | -0.002689 | 0.002564 | -0.000184 | 0.000896 | 0.001289 | -0.000536 | 0.001706 | -0.001361 | -0.000340 |
| HHD6 | 0.446354 | -0.853334 | 0.013062 | 0.166766 | 0.088198 | 0.051106 | -0.098518 | -0.103753 | -0.023426 | 0.028908 | 0.028200 | -0.031010 | 0.006127 | -0.055812 | -0.008160 | 0.057373 | -0.005498 | 0.013919 | 0.039825 | -0.019038 | -0.018515 | -0.011075 | 0.004225 | 0.000652 | -0.013215 | 0.000057 | -0.002870 | 0.003474 | 0.012218 | -0.001727 | 0.000386 | 0.013032 | -0.000984 | 0.001028 | -0.000793 | -0.013763 | -0.000832 | 0.000111 | -0.001358 | 0.005424 | 0.000051 | 0.006825 | 0.003625 | -0.003963 | -0.005457 | -0.001429 | -0.000588 | -0.004158 | -0.000656 | -0.001849 | -0.002451 | 0.001143 | 0.001835 | -0.002889 | -0.000388 | 0.003727 | 0.001298 | 0.001429 | 0.005350 | 0.000086 | 0.003541 | -0.003246 | 0.002417 | 0.002831 | 0.005759 | 0.000937 | -0.000897 | 0.002543 | -0.003756 | -0.000795 | -0.000720 | -0.000978 | 0.000867 | -0.002683 | 0.001363 | -0.000626 |
| HHD7 | 0.636692 | 0.150731 | -0.656035 | -0.174739 | 0.217019 | -0.046240 | 0.173072 | -0.122501 | 0.003765 | -0.012724 | -0.067488 | 0.025655 | -0.003299 | -0.020005 | 0.016123 | -0.049907 | -0.027595 | -0.007573 | 0.027310 | 0.016445 | 0.015192 | 0.018296 | 0.023316 | -0.009289 | 0.007458 | 0.026602 | -0.005288 | 0.002604 | 0.015804 | -0.015360 | 0.014993 | -0.007257 | 0.015315 | 0.014160 | -0.005117 | 0.015776 | 0.009940 | 0.004393 | 0.004718 | -0.012861 | -0.008542 | -0.003764 | 0.000658 | 0.003326 | 0.008399 | -0.004112 | -0.000564 | 0.003023 | -0.001440 | -0.009254 | 0.002387 | -0.004064 | -0.002865 | 0.005996 | 0.001602 | 0.002515 | -0.000252 | 0.002389 | -0.005703 | 0.001468 | -0.008438 | -0.000401 | -0.005202 | -0.002673 | -0.004545 | -0.000395 | 0.005954 | -0.000941 | 0.015707 | -0.005163 | 0.008790 | -0.001466 | -0.002183 | 0.005930 | -0.001035 | 0.001358 |
| HHD8 | 0.444873 | 0.337783 | -0.753849 | -0.138899 | 0.080129 | -0.215813 | -0.059111 | -0.047411 | -0.055237 | 0.019462 | -0.072194 | 0.053510 | -0.024679 | -0.046294 | 0.027768 | -0.019069 | -0.027293 | 0.014980 | 0.032042 | -0.003818 | 0.025995 | 0.015370 | 0.047359 | -0.019397 | -0.011368 | 0.017378 | 0.000202 | -0.000215 | 0.056319 | -0.021835 | 0.028243 | -0.004492 | 0.010010 | -0.002580 | 0.016269 | 0.010887 | -0.003121 | -0.009858 | 0.006632 | -0.016717 | 0.002417 | -0.001294 | 0.000402 | 0.005704 | 0.019447 | 0.011799 | -0.005682 | -0.016065 | -0.004720 | -0.026162 | 0.003346 | -0.002229 | -0.002575 | 0.011203 | 0.002240 | 0.013946 | 0.006438 | 0.004225 | -0.015061 | -0.002581 | 0.013404 | -0.005508 | 0.006652 | 0.006238 | -0.009470 | -0.007442 | 0.021369 | 0.005566 | 0.014856 | 0.002625 | -0.005607 | -0.021729 | 0.004077 | 0.009364 | 0.004755 | 0.002975 |
| HHD9 | 0.657552 | 0.110145 | -0.622001 | -0.176632 | 0.237927 | -0.011384 | 0.212856 | -0.134252 | 0.014512 | -0.018628 | -0.065476 | 0.019895 | 0.000823 | -0.014929 | 0.013509 | -0.054800 | -0.027013 | -0.011652 | 0.025841 | 0.019717 | 0.012923 | 0.018448 | 0.018348 | -0.007361 | 0.010804 | 0.027814 | -0.006327 | 0.003162 | 0.007981 | -0.014033 | 0.012193 | -0.007556 | 0.016287 | 0.017030 | -0.009158 | 0.016277 | 0.011973 | 0.006972 | 0.004301 | -0.011981 | -0.010359 | -0.004070 | 0.000732 | 0.002647 | 0.006290 | -0.006948 | 0.000450 | 0.006368 | -0.000860 | -0.006196 | 0.002213 | -0.004492 | -0.002797 | 0.004884 | 0.001433 | 0.000444 | -0.001325 | 0.001986 | -0.003767 | 0.002132 | -0.012132 | 0.000456 | -0.007154 | -0.004247 | -0.003710 | 0.000945 | 0.003120 | -0.002099 | 0.015480 | -0.006671 | 0.011282 | 0.002121 | -0.003423 | 0.005446 | -0.002173 | 0.000891 |
| HHD10 | 0.443019 | -0.775832 | -0.279282 | 0.225640 | 0.059720 | 0.020296 | -0.156698 | -0.151952 | 0.015014 | 0.097347 | -0.051930 | 0.036174 | -0.021524 | -0.029273 | 0.015939 | 0.015751 | -0.005870 | -0.005184 | -0.003382 | -0.000568 | -0.009114 | -0.014988 | -0.002417 | 0.016163 | -0.026720 | -0.012531 | -0.004410 | 0.015260 | 0.009313 | 0.004543 | -0.006250 | 0.016532 | -0.010730 | -0.004340 | 0.011205 | -0.025793 | -0.010033 | -0.012212 | -0.001938 | 0.011616 | -0.004978 | 0.007813 | 0.005710 | -0.009577 | -0.005452 | 0.001602 | 0.000253 | -0.008571 | 0.001503 | 0.000869 | -0.005597 | -0.001445 | 0.004127 | 0.000907 | -0.002624 | 0.005389 | 0.002821 | -0.000691 | 0.003136 | -0.004641 | 0.010561 | -0.008695 | 0.005691 | 0.003710 | 0.009875 | -0.001322 | -0.002239 | 0.000332 | -0.012353 | -0.002927 | 0.003124 | -0.001322 | -0.002243 | -0.003575 | 0.005031 | 0.000275 |
| HHD11 | 0.574492 | -0.741310 | 0.202935 | 0.061629 | 0.249408 | 0.050254 | -0.025021 | -0.043698 | 0.028131 | -0.001505 | 0.015745 | -0.038156 | 0.013656 | -0.018543 | -0.000256 | -0.012985 | 0.031746 | 0.035164 | -0.005566 | -0.009166 | 0.004789 | -0.009841 | 0.004729 | 0.018351 | 0.004866 | -0.009647 | 0.002499 | -0.010687 | -0.012891 | -0.001003 | 0.002592 | 0.012382 | -0.010085 | 0.005582 | 0.001879 | 0.002137 | 0.004102 | -0.000690 | 0.006963 | 0.003419 | 0.015746 | 0.006239 | -0.007023 | -0.006902 | -0.001610 | 0.002122 | -0.003166 | -0.007956 | -0.009514 | -0.003080 | -0.000897 | 0.003026 | 0.003947 | -0.000117 | 0.005352 | 0.003975 | 0.002424 | -0.001855 | 0.006965 | 0.001786 | -0.002233 | 0.002109 | -0.001956 | 0.003513 | 0.001161 | -0.002656 | -0.003550 | 0.003012 | 0.003243 | -0.001273 | -0.003330 | 0.000188 | -0.000187 | -0.000522 | 0.000023 | -0.000026 |
| HHD12 | 0.011848 | -0.848048 | -0.389569 | 0.237063 | 0.036543 | 0.033542 | -0.145270 | -0.095716 | -0.046572 | 0.104636 | -0.054415 | 0.043264 | -0.011977 | -0.074314 | 0.048613 | 0.043885 | -0.011887 | -0.063048 | 0.014320 | 0.006294 | 0.000694 | 0.004157 | 0.012589 | 0.023927 | 0.018713 | -0.005351 | 0.003953 | 0.003010 | -0.010216 | 0.003716 | 0.011335 | 0.014332 | -0.001934 | 0.002421 | -0.007050 | -0.030429 | -0.017182 | 0.004578 | -0.008952 | -0.002150 | -0.001275 | 0.013808 | 0.002942 | 0.005264 | -0.013035 | 0.004586 | 0.001766 | -0.001081 | 0.017359 | -0.000681 | 0.005800 | -0.001326 | 0.009493 | -0.001934 | 0.011399 | 0.013101 | -0.001066 | 0.003325 | 0.003770 | -0.003497 | 0.008928 | -0.010191 | -0.000686 | 0.005271 | 0.011207 | 0.001456 | -0.008380 | 0.005909 | -0.003835 | -0.001676 | 0.000620 | -0.003696 | -0.004206 | -0.007502 | 0.009221 | 0.004059 |
| ETHC1 | -0.471733 | 0.781610 | -0.036798 | 0.304154 | -0.004108 | 0.063927 | -0.168605 | 0.022351 | -0.069076 | -0.141978 | -0.061143 | -0.021054 | -0.002970 | 0.011185 | -0.007016 | -0.015446 | -0.054330 | 0.041998 | -0.034607 | -0.010610 | -0.021147 | 0.006456 | 0.019099 | -0.005445 | 0.004592 | -0.000150 | -0.002016 | -0.002581 | -0.021798 | 0.004036 | 0.002598 | -0.001994 | 0.010921 | -0.002207 | -0.002768 | 0.014294 | 0.014899 | 0.008017 | -0.021538 | 0.002059 | -0.001236 | 0.006197 | -0.004608 | 0.008635 | 0.000696 | -0.010169 | 0.002448 | 0.005296 | -0.003313 | 0.000597 | 0.001761 | -0.002773 | -0.001807 | 0.003026 | -0.004579 | -0.002190 | -0.002936 | 0.002580 | -0.000149 | 0.003302 | -0.004774 | -0.002712 | -0.001708 | -0.008391 | -0.001141 | 0.005600 | -0.001036 | -0.002426 | 0.006446 | 0.000376 | 0.002020 | -0.001072 | 0.000924 | -0.005689 | -0.004553 | -0.000330 |
| ETHC2 | -0.734783 | 0.172279 | 0.153007 | 0.532661 | 0.019540 | 0.139465 | -0.267273 | -0.053507 | 0.008327 | -0.064687 | -0.007551 | 0.103986 | 0.010012 | -0.039447 | 0.011698 | 0.052823 | -0.031431 | 0.026864 | -0.053947 | -0.009195 | -0.019782 | -0.003828 | -0.004796 | 0.026857 | -0.008300 | 0.001352 | -0.015079 | 0.008479 | -0.013603 | 0.017459 | 0.013359 | 0.018036 | 0.013280 | 0.002356 | -0.017467 | 0.005756 | 0.011627 | 0.009151 | -0.007282 | 0.010028 | -0.004961 | 0.002705 | -0.010120 | 0.009030 | 0.001740 | -0.008040 | 0.006955 | 0.004898 | 0.004121 | 0.000533 | 0.000960 | -0.001905 | -0.000900 | 0.003213 | -0.000415 | 0.000387 | -0.001300 | 0.003732 | -0.002968 | -0.001023 | 0.003254 | -0.003369 | -0.001381 | -0.005265 | 0.003731 | 0.003110 | -0.001596 | -0.006712 | 0.005165 | -0.002672 | 0.002057 | 0.004847 | -0.003562 | -0.007092 | -0.001176 | 0.001772 |
| ETHC3 | 0.308266 | -0.297016 | 0.880798 | 0.038981 | 0.074921 | -0.146933 | -0.025377 | 0.070921 | -0.033979 | -0.052430 | 0.013314 | -0.025654 | -0.004376 | 0.005845 | -0.010644 | 0.014616 | -0.004462 | 0.005004 | 0.010378 | -0.000215 | 0.005100 | 0.010155 | 0.006635 | 0.001718 | 0.011911 | -0.004017 | 0.002912 | -0.001836 | 0.002823 | -0.006063 | 0.003773 | -0.002408 | -0.005353 | 0.001116 | -0.003356 | 0.005888 | -0.002760 | -0.002867 | -0.004114 | -0.006297 | -0.000857 | -0.001316 | -0.000395 | 0.000984 | -0.004135 | 0.002439 | 0.002452 | 0.002230 | 0.001045 | -0.001517 | 0.005528 | 0.000872 | 0.001751 | -0.001943 | 0.003986 | -0.000127 | -0.001266 | 0.001666 | 0.000137 | 0.003761 | -0.000343 | 0.003596 | -0.000348 | -0.002447 | -0.002780 | -0.000235 | 0.000736 | 0.001135 | 0.005309 | 0.000998 | 0.000531 | -0.003024 | -0.000278 | -0.000730 | -0.001706 | 0.003150 |
| ETHC4 | 0.587527 | 0.074885 | -0.469121 | -0.296492 | 0.204475 | 0.063004 | 0.434758 | -0.215019 | 0.158040 | 0.105949 | -0.042271 | -0.038671 | -0.039244 | 0.026230 | 0.006359 | -0.034375 | 0.039096 | -0.036156 | 0.093113 | 0.019878 | 0.021877 | -0.007621 | -0.008013 | 0.002901 | 0.015809 | -0.000341 | 0.005044 | -0.007233 | -0.007670 | 0.000691 | -0.023078 | -0.026480 | 0.008187 | 0.011796 | 0.018169 | -0.005958 | -0.012693 | -0.003726 | -0.002629 | -0.002103 | -0.005310 | -0.000320 | 0.011052 | -0.012417 | -0.007833 | -0.002804 | 0.006809 | -0.000791 | -0.008736 | 0.009252 | 0.003286 | -0.001109 | 0.000974 | 0.003017 | 0.003584 | -0.003005 | -0.000966 | 0.003787 | -0.000184 | 0.001807 | -0.005493 | -0.003748 | -0.002179 | -0.001860 | -0.003731 | -0.001191 | -0.003652 | -0.002178 | -0.000620 | 0.001921 | 0.000029 | -0.003762 | 0.006125 | 0.000471 | 0.003374 | -0.003138 |
| ETHC5 | 0.555558 | -0.014420 | -0.463735 | -0.302758 | 0.216165 | 0.081070 | 0.445647 | -0.217247 | 0.179810 | 0.157204 | -0.012698 | -0.040697 | -0.059057 | 0.017632 | 0.012206 | -0.011985 | 0.054670 | -0.032991 | 0.109013 | 0.008458 | 0.024073 | -0.018742 | -0.018636 | -0.009786 | 0.010541 | -0.009231 | 0.002669 | -0.000049 | -0.002429 | 0.006176 | -0.024646 | -0.028183 | 0.004499 | 0.007387 | 0.026222 | -0.020041 | -0.012722 | -0.008868 | -0.002774 | 0.001996 | -0.004829 | -0.004328 | 0.014151 | -0.013086 | -0.003221 | 0.003640 | 0.003089 | -0.005681 | -0.008417 | 0.011356 | 0.001422 | 0.002686 | -0.000797 | 0.003432 | 0.002395 | -0.003524 | 0.000518 | 0.000546 | -0.000252 | 0.001259 | -0.002075 | -0.005187 | 0.006565 | 0.001975 | -0.003688 | -0.001914 | -0.005362 | 0.001822 | -0.011001 | 0.003302 | -0.004514 | -0.002879 | 0.007933 | -0.001626 | 0.001854 | -0.004434 |
| ETHC6 | 0.650611 | 0.024978 | -0.208605 | -0.399562 | 0.205856 | 0.084020 | 0.416363 | -0.220696 | 0.190707 | 0.147603 | -0.028873 | -0.076550 | -0.064544 | -0.007508 | 0.018396 | -0.016513 | 0.058760 | -0.030008 | 0.094384 | -0.008537 | 0.032507 | -0.009637 | -0.040015 | -0.005322 | -0.012222 | -0.024347 | -0.002810 | -0.017649 | -0.026746 | 0.019195 | -0.033173 | -0.006699 | 0.002356 | 0.007862 | 0.024776 | -0.028204 | -0.013630 | -0.000807 | -0.003174 | 0.011994 | 0.012226 | -0.001383 | 0.010599 | -0.005609 | 0.001099 | -0.002599 | -0.008796 | -0.014570 | -0.007264 | 0.015149 | -0.001770 | 0.004652 | -0.001182 | 0.006104 | -0.006167 | -0.004550 | -0.001588 | -0.007273 | -0.001162 | -0.009140 | 0.000871 | -0.007649 | 0.007741 | 0.004771 | 0.000763 | -0.001980 | -0.001714 | 0.000008 | -0.024097 | 0.002632 | -0.005337 | 0.001194 | 0.007922 | -0.002222 | 0.001859 | -0.010362 |
| HVP1 | -0.706895 | -0.567362 | 0.021521 | -0.328256 | -0.097596 | -0.088177 | -0.132175 | -0.086999 | 0.003544 | 0.064211 | -0.071700 | -0.003116 | 0.096485 | -0.020730 | 0.023006 | 0.007279 | -0.000943 | 0.023127 | 0.026119 | -0.003983 | 0.030103 | -0.020148 | 0.016035 | -0.005873 | 0.022591 | -0.006877 | -0.008170 | 0.007062 | -0.020674 | 0.009984 | -0.006202 | -0.013449 | -0.007132 | 0.003445 | 0.007505 | 0.015524 | 0.005636 | 0.020048 | 0.014599 | 0.010328 | -0.011381 | -0.004243 | 0.007788 | 0.010841 | -0.001414 | -0.006637 | 0.006893 | 0.012003 | -0.000238 | 0.003604 | 0.006590 | -0.005489 | 0.009086 | -0.000210 | -0.004660 | -0.003181 | -0.010651 | 0.000946 | 0.002591 | 0.004145 | -0.003385 | -0.001884 | -0.014268 | -0.000446 | -0.005666 | 0.004741 | -0.002307 | 0.009846 | -0.000030 | -0.000426 | 0.004701 | 0.000822 | 0.006271 | 0.003190 | -0.001715 | 0.004033 |
| HVP2 | -0.745553 | -0.547668 | -0.023699 | -0.288641 | -0.098065 | -0.126283 | -0.112109 | -0.062210 | -0.005238 | 0.052542 | -0.056311 | -0.019394 | 0.065499 | -0.033919 | 0.020247 | 0.009058 | -0.008293 | 0.022073 | 0.024363 | -0.000794 | 0.035289 | -0.003506 | -0.005056 | 0.002487 | 0.009929 | -0.005935 | -0.003144 | -0.001188 | -0.018049 | 0.001704 | -0.004536 | -0.014801 | -0.002199 | 0.000898 | 0.011272 | 0.007706 | 0.007256 | 0.012259 | 0.017784 | 0.009214 | -0.006605 | -0.004046 | -0.000473 | 0.009540 | 0.000493 | -0.007535 | 0.003859 | 0.002827 | -0.003822 | 0.002619 | 0.004031 | -0.006391 | 0.003270 | -0.000520 | 0.000725 | 0.002442 | -0.007429 | 0.002697 | -0.004068 | 0.003514 | -0.003281 | -0.002890 | -0.011916 | -0.000569 | -0.002197 | 0.002437 | -0.000292 | 0.005782 | 0.000907 | -0.002011 | 0.002131 | -0.002858 | 0.004983 | -0.000893 | -0.003034 | 0.008561 |
| HVP3 | -0.817129 | -0.500195 | -0.042655 | -0.183490 | -0.094325 | -0.143992 | -0.065537 | -0.035525 | -0.006985 | 0.033598 | -0.027883 | -0.033119 | 0.009825 | -0.038970 | 0.013397 | 0.010441 | -0.020484 | 0.015988 | 0.013651 | 0.000699 | 0.034645 | 0.016406 | -0.021719 | 0.011478 | -0.007884 | 0.000763 | -0.001735 | -0.017204 | -0.013481 | -0.004217 | -0.007274 | -0.012721 | 0.005135 | -0.001402 | 0.011842 | -0.003850 | 0.006979 | 0.003598 | 0.016809 | 0.002370 | 0.001122 | -0.005359 | -0.007115 | 0.006921 | 0.001689 | -0.006062 | 0.002014 | -0.005099 | -0.005276 | 0.002006 | -0.000004 | -0.007503 | -0.002354 | 0.002781 | 0.004897 | 0.005094 | -0.003301 | 0.003442 | -0.010673 | 0.000102 | -0.002163 | -0.003989 | -0.007307 | -0.000340 | 0.002317 | -0.001148 | -0.000070 | -0.001268 | 0.001570 | -0.001245 | -0.002011 | -0.004272 | -0.000189 | -0.004107 | -0.001999 | 0.008484 |
| HVP4 | -0.866637 | -0.451891 | -0.052272 | -0.060770 | -0.066580 | -0.145281 | -0.024653 | -0.001383 | -0.009828 | 0.032107 | 0.004693 | -0.030660 | -0.034319 | -0.037935 | 0.010129 | 0.010701 | -0.021654 | 0.010115 | 0.007481 | -0.003627 | 0.029581 | 0.030286 | -0.019778 | 0.009983 | -0.015909 | 0.008718 | -0.000963 | -0.029914 | -0.009329 | -0.004852 | -0.015319 | -0.011695 | 0.008241 | 0.001717 | 0.008513 | -0.007874 | 0.003405 | -0.001451 | 0.013569 | -0.005852 | 0.005360 | -0.007612 | -0.006397 | 0.004673 | 0.000606 | -0.002409 | 0.003176 | -0.005333 | -0.003062 | 0.000095 | -0.001345 | -0.005456 | -0.003060 | 0.006340 | 0.005820 | 0.004360 | -0.000317 | 0.003772 | -0.011719 | -0.002937 | -0.000511 | -0.003617 | -0.003643 | -0.000171 | 0.005258 | -0.003064 | 0.000610 | -0.006354 | 0.001695 | 0.001294 | -0.003456 | -0.003215 | -0.003894 | -0.004448 | 0.001492 | 0.002687 |
| HVP5 | -0.886902 | -0.391056 | -0.065508 | 0.105791 | 0.018111 | -0.157179 | 0.009264 | 0.046931 | -0.019546 | 0.043392 | 0.033953 | -0.006626 | -0.064893 | -0.024923 | 0.007463 | 0.018246 | -0.019103 | 0.004987 | 0.006603 | -0.011846 | 0.023316 | 0.044086 | 0.003967 | -0.010820 | -0.009897 | 0.019456 | 0.001744 | -0.038715 | -0.003402 | -0.005690 | -0.025026 | -0.019320 | 0.007091 | 0.005208 | 0.002508 | -0.009070 | -0.002858 | -0.005348 | 0.008444 | -0.011986 | 0.007300 | -0.009042 | -0.002582 | 0.000226 | -0.004273 | 0.000272 | 0.003091 | -0.002866 | -0.000168 | -0.002173 | -0.000222 | 0.002064 | -0.003254 | 0.008225 | 0.006425 | 0.001870 | 0.002504 | 0.001885 | -0.007473 | -0.004488 | 0.000813 | -0.000646 | 0.002385 | 0.000155 | 0.005041 | -0.006837 | 0.002062 | -0.005335 | -0.000313 | 0.002659 | -0.002499 | -0.000052 | -0.004339 | -0.002497 | 0.001585 | -0.001979 |
| HVP6 | -0.657750 | -0.579237 | 0.121114 | -0.351267 | -0.107596 | -0.025982 | -0.135877 | -0.143602 | 0.020092 | 0.048694 | -0.093747 | 0.031443 | 0.108326 | 0.013130 | 0.020876 | 0.012255 | 0.008202 | 0.028983 | 0.028795 | -0.012719 | 0.021841 | -0.036510 | 0.050053 | -0.030725 | 0.036867 | -0.001854 | -0.003866 | 0.011702 | -0.020751 | 0.027726 | -0.007961 | -0.006159 | -0.014749 | 0.001959 | -0.003436 | 0.018913 | 0.000389 | 0.026641 | 0.012103 | 0.008985 | -0.015228 | -0.000679 | 0.016442 | 0.009374 | -0.004855 | -0.002341 | 0.011236 | 0.022854 | 0.004000 | 0.005098 | 0.005678 | -0.004775 | 0.013743 | 0.003790 | -0.010872 | -0.011547 | -0.010104 | -0.002636 | 0.012827 | 0.002132 | -0.001792 | -0.000765 | -0.011268 | 0.000963 | -0.006923 | 0.006343 | -0.005304 | 0.013137 | -0.000604 | 0.004280 | 0.006724 | 0.004309 | 0.005417 | 0.007489 | 0.001243 | -0.006442 |
| HUR1 | 0.534193 | -0.695899 | -0.347590 | -0.025862 | -0.051676 | -0.166572 | -0.179907 | -0.113523 | -0.065451 | 0.034173 | 0.067578 | -0.004085 | -0.045175 | -0.007090 | -0.021509 | -0.011437 | -0.007676 | 0.047017 | -0.021205 | -0.020227 | -0.021746 | 0.014809 | 0.009408 | -0.014560 | -0.077172 | -0.031708 | 0.003759 | -0.009546 | -0.000366 | 0.010894 | -0.017596 | -0.022602 | -0.012271 | -0.011804 | 0.012023 | 0.004708 | 0.005734 | -0.007215 | 0.010144 | 0.003428 | 0.007945 | -0.002384 | 0.021576 | 0.002106 | -0.004869 | 0.000072 | 0.007326 | 0.004849 | 0.001960 | -0.005053 | -0.001929 | -0.001474 | 0.002211 | 0.007102 | -0.014077 | -0.000815 | -0.002814 | -0.016876 | 0.004894 | -0.011027 | 0.003748 | -0.004525 | 0.013309 | -0.007683 | 0.007275 | -0.001841 | 0.010166 | -0.008979 | -0.009954 | 0.009498 | 0.000044 | -0.006937 | -0.002917 | -0.005842 | -0.009858 | -0.009540 |
| HUR2 | -0.862128 | 0.418053 | 0.190228 | -0.098385 | 0.093211 | 0.133053 | 0.068634 | 0.006160 | -0.020137 | -0.018675 | -0.001758 | -0.010682 | -0.016482 | 0.013492 | -0.007252 | 0.009695 | -0.011379 | -0.012661 | 0.014226 | -0.015828 | -0.017679 | 0.012622 | -0.020575 | 0.011522 | -0.003650 | 0.000488 | -0.010775 | -0.005273 | -0.004805 | 0.011973 | -0.001018 | -0.007897 | 0.003972 | -0.008198 | -0.012704 | -0.001987 | -0.002656 | 0.001046 | -0.007607 | -0.005366 | 0.004250 | -0.004173 | 0.001799 | -0.002364 | 0.003034 | 0.006232 | -0.002400 | -0.005647 | -0.001411 | 0.000483 | -0.000637 | -0.000176 | 0.000706 | -0.000144 | -0.000019 | -0.002163 | -0.000281 | 0.004671 | 0.000482 | 0.002052 | -0.002774 | -0.002717 | -0.001898 | 0.001610 | -0.001852 | 0.004946 | -0.001119 | -0.000659 | -0.002804 | 0.000676 | 0.000016 | 0.000096 | 0.003422 | 0.000861 | 0.001816 | 0.000853 |
| RHP1 | -0.854241 | 0.404618 | 0.221646 | -0.052510 | 0.170979 | 0.104507 | 0.036038 | -0.084169 | -0.030102 | -0.034955 | -0.002158 | -0.013862 | -0.010506 | 0.021592 | -0.007749 | 0.005488 | -0.017912 | -0.011883 | 0.008520 | -0.014253 | -0.012591 | 0.016084 | -0.016600 | 0.002776 | -0.002263 | 0.003306 | -0.012003 | -0.000309 | -0.004811 | 0.004992 | 0.000539 | -0.005434 | 0.000034 | -0.006950 | -0.007970 | -0.006440 | -0.006062 | -0.001749 | -0.006015 | -0.006270 | 0.007862 | -0.001204 | -0.002457 | -0.005553 | 0.004474 | 0.005259 | -0.005399 | -0.007402 | -0.003175 | 0.000656 | -0.001578 | 0.001204 | 0.001033 | 0.000447 | 0.003931 | -0.001687 | 0.002648 | 0.004989 | -0.001023 | 0.002440 | -0.002032 | -0.002385 | 0.000276 | 0.001279 | -0.000512 | 0.005152 | -0.002337 | -0.001632 | -0.002128 | -0.000014 | -0.000306 | 0.000551 | 0.002374 | 0.003916 | 0.001278 | 0.003760 |
| RHP2 | -0.812433 | 0.471377 | 0.246090 | -0.031902 | 0.192393 | 0.090993 | 0.053927 | -0.060667 | -0.009706 | -0.030297 | -0.013841 | -0.008925 | -0.003406 | 0.018621 | -0.007954 | 0.013021 | -0.010160 | -0.019800 | 0.007271 | -0.006829 | -0.012699 | 0.009079 | -0.016146 | 0.005901 | 0.006136 | 0.004702 | -0.010150 | -0.001857 | -0.001405 | 0.006201 | 0.003915 | -0.000325 | 0.002299 | -0.004194 | -0.010873 | -0.006270 | -0.003073 | 0.000259 | -0.007436 | -0.004187 | 0.003444 | -0.002725 | -0.002832 | -0.002840 | 0.004893 | 0.004604 | -0.003865 | -0.004909 | -0.000147 | 0.001147 | 0.000357 | 0.000168 | 0.000320 | -0.000689 | 0.003271 | -0.001495 | 0.000753 | 0.005403 | -0.000536 | 0.002453 | -0.002599 | -0.001947 | -0.001561 | 0.001591 | -0.002683 | 0.004763 | -0.003881 | -0.000200 | -0.000933 | -0.000514 | 0.000085 | 0.000905 | 0.002999 | 0.002549 | 0.001838 | 0.002420 |
| RHP3 | -0.513289 | 0.714513 | -0.387494 | -0.110656 | 0.180833 | -0.147780 | 0.005532 | -0.049296 | -0.029010 | -0.034017 | 0.030378 | -0.010894 | -0.011422 | 0.012984 | -0.023474 | 0.022142 | -0.011743 | -0.014750 | 0.009432 | 0.009419 | -0.005743 | 0.002824 | 0.012847 | -0.001471 | -0.000082 | 0.001707 | 0.011496 | -0.010834 | 0.012667 | -0.006966 | 0.002530 | -0.003065 | -0.006504 | -0.003687 | -0.003992 | 0.002745 | -0.000904 | 0.006413 | -0.001453 | 0.000386 | -0.007008 | -0.006719 | -0.000465 | 0.005387 | -0.004579 | 0.001452 | 0.008419 | 0.007841 | 0.000757 | 0.001607 | 0.005519 | -0.000154 | 0.003467 | -0.003378 | 0.004092 | -0.000424 | -0.001970 | -0.001376 | 0.001867 | 0.000949 | -0.000033 | 0.000322 | -0.002158 | -0.000542 | 0.000780 | 0.001464 | -0.002944 | 0.000718 | -0.000800 | 0.000641 | -0.003323 | 0.000003 | 0.004053 | -0.003041 | -0.004743 | -0.002155 |
| RHP4 | 0.171036 | 0.266582 | -0.827062 | -0.176677 | 0.272830 | -0.266067 | -0.126662 | 0.014048 | -0.046163 | -0.021069 | 0.079101 | 0.003345 | 0.017227 | -0.009221 | -0.016129 | 0.020305 | 0.036869 | 0.035829 | -0.003263 | 0.013655 | 0.010264 | 0.036859 | 0.023248 | -0.023932 | 0.003451 | 0.013483 | -0.007553 | -0.050270 | 0.001786 | 0.021784 | 0.005028 | -0.005061 | 0.006801 | -0.010278 | -0.002340 | 0.002678 | 0.000485 | 0.001321 | 0.004500 | 0.002941 | -0.002792 | -0.010480 | 0.004278 | 0.014149 | 0.008404 | 0.002106 | -0.000689 | -0.000673 | 0.004243 | -0.002366 | -0.005270 | -0.003155 | -0.011954 | -0.003084 | 0.007861 | 0.016997 | -0.002549 | -0.008331 | 0.004702 | -0.014727 | 0.001496 | -0.007468 | 0.003415 | 0.004049 | 0.008162 | -0.001432 | 0.008714 | -0.002614 | -0.004323 | -0.002113 | -0.003058 | -0.007432 | -0.003463 | 0.001622 | 0.001728 | -0.003830 |
| HUPA1 | 0.478817 | -0.706928 | -0.391901 | 0.098105 | 0.194559 | 0.085501 | -0.017768 | -0.067966 | 0.005009 | -0.053943 | -0.022202 | 0.023747 | -0.016604 | 0.054509 | -0.014588 | -0.004339 | -0.105703 | -0.048675 | -0.059838 | -0.062753 | 0.101095 | 0.036711 | -0.027382 | 0.012017 | 0.058517 | 0.071988 | -0.017974 | 0.013497 | 0.009249 | -0.029012 | -0.034131 | 0.018227 | -0.009956 | 0.015049 | 0.000819 | 0.014113 | -0.020344 | 0.015810 | 0.001240 | -0.018252 | 0.005610 | -0.018557 | -0.007456 | 0.015484 | 0.006853 | 0.002580 | -0.002785 | 0.003501 | 0.000636 | 0.017417 | -0.003930 | 0.000909 | -0.003127 | -0.008740 | -0.003692 | -0.008840 | -0.004651 | 0.001986 | -0.000819 | -0.000569 | -0.002151 | 0.005488 | -0.006116 | 0.002594 | -0.004906 | 0.003552 | 0.001775 | -0.007991 | -0.011017 | -0.000974 | -0.011928 | 0.006954 | 0.002500 | 0.006747 | 0.000075 | 0.001919 |
| HUPA2 | 0.198933 | -0.914523 | -0.172529 | 0.182491 | 0.010579 | -0.067508 | -0.056726 | -0.086697 | 0.066777 | -0.002066 | 0.125038 | 0.004338 | -0.036417 | 0.029321 | -0.042926 | -0.064831 | -0.004756 | 0.077239 | 0.015724 | 0.047230 | -0.030757 | 0.005662 | -0.000089 | -0.020311 | -0.036136 | -0.014195 | 0.037011 | 0.004287 | -0.003799 | 0.019576 | -0.002030 | -0.032256 | 0.004515 | -0.035039 | -0.002047 | 0.006388 | 0.005402 | 0.001700 | -0.006353 | 0.002840 | -0.007372 | 0.000668 | 0.003802 | -0.001179 | -0.004120 | -0.001020 | 0.004081 | 0.007107 | 0.002811 | 0.000045 | 0.004913 | -0.004893 | -0.004925 | -0.001438 | -0.001958 | -0.001834 | -0.002991 | 0.006462 | -0.007616 | 0.003789 | -0.003955 | -0.000731 | -0.001737 | -0.002352 | -0.001330 | 0.003355 | 0.000328 | -0.001351 | -0.000353 | 0.003842 | 0.005248 | -0.003845 | 0.006971 | -0.000142 | 0.002327 | 0.002181 |
| HUPA3 | 0.542799 | 0.552591 | 0.265304 | 0.205524 | -0.308272 | -0.287299 | -0.033733 | -0.147715 | 0.068070 | 0.070948 | -0.042162 | 0.002159 | 0.044957 | -0.057699 | 0.013656 | 0.091528 | 0.044292 | 0.017493 | -0.060835 | 0.038614 | 0.007128 | -0.002897 | 0.047250 | -0.111383 | 0.026969 | -0.016360 | -0.100476 | -0.093324 | -0.021611 | -0.059522 | -0.006799 | 0.024767 | -0.023886 | 0.050539 | 0.035021 | -0.025691 | 0.000312 | -0.031390 | -0.021660 | -0.006417 | -0.013818 | 0.000023 | 0.008621 | -0.028692 | -0.004812 | 0.003510 | 0.015486 | -0.009330 | -0.011620 | -0.017337 | -0.004643 | -0.008013 | 0.037311 | 0.018495 | 0.009171 | 0.013768 | -0.009401 | -0.016783 | 0.001909 | 0.008179 | 0.022080 | -0.004543 | 0.002186 | -0.016290 | 0.006074 | -0.005052 | -0.009271 | 0.003790 | 0.011902 | -0.014301 | 0.006675 | -0.006246 | -0.000442 | -0.007822 | -0.007070 | -0.000568 |
| HUPA4 | 0.653654 | 0.401987 | -0.350659 | -0.230373 | 0.185080 | -0.038097 | -0.046379 | -0.036090 | -0.293223 | 0.045605 | -0.171772 | 0.009704 | 0.080168 | -0.054609 | 0.053257 | -0.019546 | 0.069139 | -0.029767 | 0.088238 | -0.056621 | -0.018088 | -0.040862 | -0.014715 | 0.131573 | 0.016827 | 0.005935 | 0.061595 | 0.024859 | 0.049577 | 0.005404 | 0.040520 | 0.032898 | 0.025672 | 0.030900 | 0.010622 | 0.000229 | 0.011867 | -0.010379 | 0.027619 | 0.024889 | 0.014561 | 0.023599 | -0.005778 | 0.008655 | -0.006000 | -0.010767 | -0.022990 | -0.006376 | 0.003054 | -0.016453 | -0.005957 | 0.021693 | -0.027811 | 0.000665 | 0.005286 | -0.005629 | 0.016261 | -0.012880 | 0.003655 | -0.025462 | -0.005720 | 0.003739 | 0.000933 | -0.005845 | 0.006550 | -0.012261 | 0.004565 | 0.008757 | 0.014410 | 0.007372 | 0.002936 | -0.016943 | -0.022580 | -0.001665 | -0.007683 | -0.006074 |
| HUPA5 | 0.618138 | -0.532894 | -0.399772 | 0.019137 | 0.237901 | 0.135608 | -0.026087 | -0.062564 | -0.047908 | -0.070124 | -0.078750 | 0.019220 | 0.000460 | 0.041025 | -0.002782 | 0.021732 | -0.124587 | -0.072955 | -0.070451 | -0.106944 | 0.117374 | 0.050525 | -0.021438 | 0.021669 | 0.065898 | 0.080850 | -0.034896 | 0.009046 | 0.006970 | -0.039261 | -0.036519 | 0.028898 | -0.022017 | 0.030108 | -0.001263 | 0.020842 | -0.031839 | 0.016089 | -0.000484 | -0.020826 | 0.011468 | -0.023419 | -0.001074 | 0.018136 | -0.001661 | 0.005006 | -0.003797 | 0.000638 | -0.002168 | 0.018203 | -0.004967 | 0.006599 | -0.002888 | -0.008950 | -0.004738 | -0.015170 | -0.002606 | -0.000929 | 0.000696 | 0.000276 | 0.000318 | 0.007932 | -0.003931 | -0.000935 | -0.001576 | 0.004621 | 0.002076 | -0.011918 | -0.011956 | 0.001433 | -0.017852 | 0.002576 | 0.003205 | 0.004553 | -0.004300 | -0.000706 |
| HUPA6 | 0.260210 | -0.858328 | -0.325747 | 0.204986 | 0.049369 | -0.011191 | -0.063488 | -0.100283 | 0.040779 | -0.001258 | 0.097666 | 0.010430 | -0.018170 | 0.018027 | -0.038600 | -0.052965 | -0.013408 | 0.067049 | -0.000771 | 0.032595 | -0.017524 | 0.020711 | -0.017883 | -0.023347 | -0.025866 | -0.005386 | 0.016054 | 0.010145 | -0.010988 | 0.018142 | -0.023083 | -0.043353 | 0.011755 | -0.045861 | -0.001163 | 0.000452 | -0.000586 | 0.000355 | 0.003831 | -0.008391 | -0.006539 | -0.004134 | 0.005378 | -0.000063 | 0.003026 | 0.004482 | 0.007801 | 0.006349 | 0.004564 | -0.000863 | 0.003537 | -0.002392 | -0.000983 | 0.001180 | -0.000112 | -0.000197 | -0.002473 | 0.004300 | -0.008025 | -0.000001 | 0.000002 | 0.003497 | -0.001735 | -0.004225 | -0.000203 | -0.002619 | 0.001646 | -0.001525 | 0.000030 | -0.005368 | 0.005324 | 0.002700 | 0.001120 | 0.003767 | 0.006923 | 0.002860 |
| HUPA7 | 0.550575 | 0.624946 | 0.092018 | 0.186120 | -0.315872 | -0.177785 | -0.049846 | -0.204513 | 0.022649 | 0.067014 | -0.047955 | 0.038319 | 0.065611 | -0.037537 | 0.001768 | 0.100601 | 0.054250 | 0.035366 | -0.057881 | 0.026955 | 0.011412 | -0.015528 | 0.044174 | -0.081442 | 0.006618 | -0.004096 | -0.099896 | -0.102947 | 0.000863 | -0.046057 | -0.011174 | 0.012950 | -0.013004 | 0.053670 | 0.045703 | -0.033440 | 0.010238 | -0.024488 | -0.017920 | -0.004647 | -0.026122 | 0.004686 | 0.004322 | -0.031196 | -0.006465 | 0.002082 | -0.001118 | -0.016382 | -0.018779 | -0.021127 | -0.011443 | -0.009057 | 0.023102 | 0.020335 | 0.011149 | 0.014941 | -0.006143 | -0.014706 | -0.002542 | 0.002906 | 0.020650 | -0.014766 | -0.006058 | -0.017787 | 0.011710 | -0.006655 | -0.008114 | 0.002264 | 0.016081 | -0.012434 | 0.012196 | -0.015379 | -0.009830 | -0.008048 | -0.010241 | -0.000593 |
| RP1 | -0.855315 | -0.451658 | -0.119953 | -0.116531 | -0.015520 | -0.148633 | -0.001297 | 0.062612 | -0.006030 | 0.021785 | -0.017945 | -0.027866 | 0.000977 | -0.036295 | 0.009210 | -0.008757 | -0.007971 | 0.002405 | 0.039690 | 0.011700 | 0.008163 | -0.012913 | -0.012107 | 0.030917 | 0.006095 | -0.014309 | 0.005790 | -0.010333 | 0.007065 | 0.000497 | 0.017735 | 0.005035 | 0.011246 | 0.010727 | 0.002584 | 0.001828 | 0.001833 | 0.010105 | -0.007991 | 0.000901 | -0.000710 | 0.000868 | -0.000896 | 0.004658 | -0.001255 | 0.000773 | 0.012649 | 0.007053 | 0.002241 | -0.003192 | 0.006715 | -0.010059 | 0.003821 | 0.001693 | -0.000144 | 0.002544 | -0.009680 | 0.000373 | -0.000875 | -0.002633 | 0.004115 | -0.004079 | -0.012318 | 0.000120 | 0.001153 | -0.000262 | -0.009078 | -0.002597 | 0.005318 | -0.002783 | -0.000065 | -0.009935 | 0.001278 | -0.009306 | 0.006224 | -0.002238 |
| RP2 | -0.825495 | -0.499120 | -0.163276 | -0.023049 | 0.033421 | -0.152639 | 0.020274 | 0.096230 | -0.005700 | 0.022096 | -0.007398 | -0.008341 | -0.030590 | -0.028049 | 0.010591 | -0.006457 | -0.015004 | -0.002217 | 0.037662 | 0.007967 | 0.005367 | -0.001293 | -0.003430 | 0.022863 | 0.009018 | -0.004786 | 0.012026 | -0.011590 | 0.009925 | -0.001301 | 0.013218 | -0.000698 | 0.015651 | 0.003334 | 0.002787 | -0.003730 | 0.001300 | 0.003738 | -0.007399 | -0.000753 | 0.004379 | 0.002533 | -0.001726 | 0.002250 | -0.002242 | 0.003726 | 0.010626 | 0.007787 | 0.005624 | -0.002450 | 0.004728 | -0.007155 | 0.000832 | 0.006352 | 0.003432 | 0.003316 | -0.006734 | -0.001399 | -0.001137 | -0.004816 | 0.005122 | -0.003251 | -0.006239 | -0.000472 | 0.002461 | -0.004707 | -0.008852 | -0.002416 | 0.005786 | -0.002351 | 0.000603 | -0.008167 | -0.001223 | -0.006764 | 0.008151 | -0.005241 |
| RP3 | -0.775381 | -0.540034 | -0.207078 | 0.075825 | 0.113511 | -0.139859 | 0.041618 | 0.120406 | -0.019352 | 0.021664 | -0.007955 | 0.023279 | -0.048496 | -0.022917 | 0.012586 | -0.000277 | -0.026940 | -0.009083 | 0.030077 | -0.000636 | 0.002492 | 0.018432 | 0.009526 | 0.003680 | 0.010297 | 0.005012 | 0.012927 | -0.007556 | 0.010085 | -0.009498 | 0.007351 | -0.010064 | 0.013879 | -0.003864 | 0.003337 | -0.009286 | 0.000107 | -0.003485 | -0.008025 | -0.001964 | 0.005383 | 0.001422 | 0.001827 | 0.001690 | -0.003629 | 0.005482 | 0.005045 | 0.005197 | 0.007264 | -0.003462 | 0.001538 | -0.000258 | -0.004867 | 0.009649 | 0.007963 | 0.002336 | -0.000624 | -0.004421 | -0.000220 | -0.005348 | 0.006368 | -0.000198 | 0.005588 | -0.001582 | 0.001797 | -0.007385 | -0.007945 | 0.001978 | 0.004866 | -0.002416 | 0.001575 | -0.007507 | -0.002167 | -0.003845 | 0.004922 | -0.005353 |
| RP4 | -0.715885 | -0.539824 | -0.242035 | 0.173587 | 0.236768 | -0.129360 | 0.037369 | 0.124195 | -0.040019 | 0.015065 | -0.019405 | 0.053152 | -0.041202 | -0.025501 | 0.018971 | 0.011241 | -0.043553 | -0.022955 | 0.017108 | -0.011535 | 0.005203 | 0.030970 | 0.024539 | -0.018009 | 0.006242 | 0.002648 | 0.010369 | -0.000257 | 0.010045 | -0.020195 | 0.004103 | -0.014610 | 0.008123 | -0.001421 | 0.003553 | -0.016188 | 0.001973 | -0.010672 | -0.009732 | 0.001685 | 0.001982 | -0.001484 | 0.008032 | 0.002273 | -0.004030 | 0.005183 | -0.002361 | 0.000692 | 0.003936 | -0.006559 | -0.002068 | 0.005405 | -0.010143 | 0.014048 | 0.013840 | -0.000280 | 0.003259 | -0.008011 | 0.001893 | -0.004784 | 0.005902 | -0.000139 | 0.014447 | -0.000122 | -0.000579 | -0.005939 | -0.009969 | 0.007750 | 0.005677 | -0.001733 | 0.003926 | -0.010196 | -0.000495 | -0.006376 | -0.004004 | -0.002140 |
| MSA | -0.587727 | -0.606711 | -0.250206 | -0.040405 | 0.049677 | -0.260805 | 0.061533 | 0.160139 | -0.054239 | 0.062806 | -0.072567 | 0.059586 | -0.017719 | -0.081437 | 0.029181 | 0.012393 | 0.010543 | 0.019550 | 0.096200 | -0.028641 | -0.065930 | 0.129170 | 0.041374 | -0.004764 | 0.070171 | 0.004586 | -0.048625 | -0.012918 | -0.075765 | -0.026402 | 0.004895 | 0.032161 | -0.026836 | -0.041704 | -0.012141 | 0.073275 | -0.041199 | 0.010355 | 0.025895 | 0.052108 | 0.018447 | 0.044635 | -0.007850 | 0.018087 | -0.010335 | -0.013918 | 0.014433 | -0.022067 | 0.007152 | -0.005628 | 0.003208 | 0.011238 | -0.017917 | -0.009781 | -0.038879 | 0.008458 | -0.012537 | 0.003613 | -0.015680 | 0.005740 | 0.021964 | 0.019937 | 0.030959 | -0.048849 | 0.000781 | 0.015989 | -0.010560 | 0.015643 | -0.007112 | -0.011713 | -0.005181 | -0.009852 | -0.014136 | 0.011516 | -0.022085 | 0.014995 |
| ADI | 0.560818 | 0.509508 | 0.283846 | 0.324447 | -0.155293 | 0.079536 | 0.225196 | -0.175450 | -0.202502 | -0.071009 | 0.037145 | 0.072209 | -0.016584 | 0.001578 | -0.014050 | -0.056614 | 0.093241 | -0.057579 | -0.034965 | -0.061365 | -0.073413 | -0.042616 | -0.013153 | -0.008363 | 0.005478 | -0.048394 | -0.023945 | -0.041393 | 0.022462 | 0.007076 | -0.034484 | 0.014726 | -0.017404 | -0.013335 | -0.026014 | -0.032690 | -0.044126 | 0.018778 | 0.021937 | -0.013832 | 0.016600 | 0.007441 | -0.006866 | -0.035553 | 0.016701 | 0.012496 | -0.013842 | -0.007806 | -0.017916 | 0.017056 | -0.001738 | -0.003284 | 0.004309 | -0.032493 | -0.005911 | -0.013879 | 0.002780 | 0.043312 | -0.000654 | 0.012592 | -0.025307 | 0.013765 | -0.033394 | 0.015763 | -0.008181 | -0.015247 | -0.002481 | 0.005826 | -0.030858 | 0.024414 | -0.015199 | 0.025590 | 0.008606 | 0.027461 | -0.000073 | 0.014635 |
| DMA | -0.388810 | -0.383270 | -0.295003 | -0.248289 | -0.067001 | -0.268542 | -0.243872 | 0.007206 | -0.455076 | 0.188006 | -0.180828 | -0.063331 | 0.047610 | -0.180160 | 0.074262 | -0.111970 | -0.086114 | 0.134158 | 0.045954 | 0.007631 | -0.014690 | 0.037359 | -0.057788 | -0.081667 | 0.075462 | -0.043747 | -0.044746 | -0.040670 | -0.041498 | 0.048017 | 0.009460 | 0.034880 | 0.019292 | 0.007027 | 0.010108 | -0.020184 | 0.001904 | 0.026831 | 0.017953 | -0.022410 | -0.003578 | 0.000206 | -0.014067 | -0.005931 | 0.037806 | -0.017544 | 0.008837 | -0.004627 | -0.010203 | 0.027323 | -0.009617 | 0.029725 | -0.014627 | -0.027303 | -0.033584 | -0.025281 | 0.015313 | 0.030559 | 0.002443 | 0.009138 | -0.013005 | 0.016262 | 0.022211 | -0.011693 | 0.006176 | -0.012471 | 0.013786 | -0.007589 | -0.033485 | 0.024599 | -0.015888 | 0.003806 | -0.006947 | -0.007947 | 0.009742 | 0.034649 |
| IC1 | -0.984702 | -0.087242 | 0.070055 | -0.113272 | 0.006042 | 0.014420 | 0.003020 | -0.032833 | 0.024281 | -0.021609 | -0.020640 | 0.016023 | 0.011656 | 0.009637 | -0.008977 | 0.010029 | -0.002493 | 0.001180 | 0.013279 | -0.004736 | 0.005780 | -0.001092 | 0.007275 | -0.016344 | -0.007927 | 0.006541 | 0.003716 | 0.005863 | 0.009963 | 0.003098 | -0.000822 | 0.000469 | -0.007196 | -0.001754 | -0.003104 | 0.000755 | -0.006575 | -0.009320 | -0.005262 | -0.001651 | 0.000570 | 0.000308 | -0.004535 | -0.001986 | -0.003193 | 0.000683 | -0.002387 | -0.002161 | 0.000673 | 0.000280 | 0.001869 | 0.001286 | 0.000173 | -0.001594 | -0.001438 | 0.002907 | 0.001797 | -0.000263 | -0.000205 | 0.002456 | 0.002507 | -0.001873 | 0.003255 | -0.000485 | -0.000773 | 0.003378 | 0.000833 | -0.001885 | 0.001293 | 0.001522 | 0.002094 | -0.003296 | -0.002090 | 0.002680 | -0.000313 | -0.003806 |
| IC2 | -0.955565 | -0.214686 | 0.138465 | -0.106748 | 0.017145 | 0.042500 | -0.010147 | -0.058177 | 0.032384 | -0.025977 | -0.012774 | 0.012768 | 0.011787 | 0.009965 | -0.009113 | 0.010235 | 0.003225 | 0.014130 | 0.009581 | -0.006856 | 0.007797 | -0.003145 | 0.010464 | -0.018127 | -0.010530 | 0.006264 | 0.008728 | 0.002303 | 0.008137 | 0.005061 | -0.002253 | 0.002566 | -0.012910 | -0.002122 | -0.001845 | 0.001409 | -0.007791 | -0.011730 | -0.003125 | -0.000012 | 0.001928 | 0.003333 | -0.005360 | -0.003227 | -0.005740 | -0.000409 | -0.002649 | -0.004022 | -0.002071 | 0.000068 | 0.000047 | 0.001569 | 0.000879 | -0.002178 | 0.000134 | 0.004884 | 0.003168 | 0.000307 | 0.001061 | 0.004485 | 0.002874 | -0.001036 | 0.003321 | 0.000379 | 0.000966 | 0.003987 | 0.002003 | -0.001540 | 0.001410 | 0.002095 | 0.002147 | -0.003520 | -0.002979 | 0.003276 | -0.000542 | -0.004416 |
| IC3 | -0.976622 | -0.137131 | 0.098281 | -0.111982 | 0.004545 | 0.011092 | 0.001317 | -0.051765 | 0.019968 | -0.021300 | -0.014835 | 0.012640 | 0.006594 | 0.007988 | -0.005528 | 0.007620 | -0.001834 | 0.000953 | 0.010393 | -0.004048 | 0.007468 | 0.000738 | 0.003322 | -0.010463 | -0.009813 | 0.007908 | 0.002505 | 0.004293 | 0.008980 | -0.001902 | -0.000034 | -0.001570 | -0.006608 | -0.002326 | 0.000440 | -0.001311 | -0.005309 | -0.007440 | -0.003647 | 0.000664 | 0.000692 | 0.000112 | -0.002984 | -0.000693 | -0.002333 | 0.000521 | -0.003236 | -0.002888 | -0.000023 | 0.000293 | 0.001174 | 0.000863 | -0.001450 | -0.001154 | 0.000077 | 0.003035 | -0.000194 | 0.000440 | -0.000359 | 0.000021 | 0.000410 | -0.000969 | 0.003284 | -0.000781 | -0.000342 | 0.000691 | 0.001560 | -0.002320 | 0.000940 | 0.000750 | 0.000573 | -0.001978 | -0.000822 | 0.002171 | -0.001249 | -0.001919 |
| IC4 | -0.946953 | -0.243696 | 0.157548 | -0.099182 | 0.015414 | 0.035059 | -0.009679 | -0.069160 | 0.026688 | -0.023163 | -0.006183 | 0.008376 | 0.005679 | 0.008031 | -0.005164 | 0.008112 | 0.002936 | 0.010579 | 0.007097 | -0.006142 | 0.009385 | -0.000761 | 0.004993 | -0.011344 | -0.012100 | 0.007111 | 0.006092 | 0.001151 | 0.007352 | -0.001201 | -0.001524 | -0.000403 | -0.010950 | -0.003251 | 0.002051 | -0.001766 | -0.006365 | -0.008655 | -0.001875 | 0.002270 | 0.002449 | 0.002270 | -0.003450 | -0.001800 | -0.004665 | 0.000117 | -0.003476 | -0.004627 | -0.002213 | -0.000055 | 0.000191 | 0.001244 | -0.000954 | -0.001631 | 0.001174 | 0.004249 | 0.000406 | 0.000399 | 0.000561 | 0.000896 | 0.000282 | -0.000590 | 0.003178 | -0.000108 | 0.001128 | 0.000607 | 0.002413 | -0.002266 | 0.000717 | 0.001048 | 0.000046 | -0.001984 | -0.001067 | 0.002657 | -0.001568 | -0.002025 |
| IC5 | -0.818733 | -0.450025 | 0.301586 | -0.098059 | -0.018618 | 0.029768 | -0.014920 | -0.111694 | 0.038311 | -0.032609 | -0.044531 | 0.046155 | 0.008279 | 0.027223 | -0.004320 | 0.002113 | 0.019847 | 0.015934 | 0.016416 | -0.008137 | 0.008217 | -0.003851 | 0.018945 | -0.030066 | -0.001581 | 0.011580 | 0.021137 | 0.005212 | 0.017578 | 0.014244 | -0.003388 | 0.008942 | -0.011932 | 0.004160 | -0.010232 | -0.000913 | -0.006637 | -0.012498 | 0.002501 | -0.000114 | -0.000442 | 0.002029 | -0.007682 | -0.001270 | -0.003714 | -0.003055 | -0.003247 | -0.003187 | 0.000479 | -0.000008 | -0.002774 | 0.002115 | 0.001261 | -0.003359 | 0.001857 | 0.006421 | 0.008645 | 0.002597 | -0.001850 | 0.007071 | 0.006944 | -0.001267 | 0.004867 | 0.003082 | 0.003663 | 0.009439 | 0.002221 | -0.000629 | 0.001495 | 0.004283 | 0.005276 | -0.004546 | -0.005611 | 0.002827 | -0.000540 | -0.010095 |
| IC6 | 0.975380 | 0.065617 | 0.039657 | -0.064549 | 0.068128 | -0.021930 | -0.008365 | -0.157054 | -0.021052 | -0.042346 | -0.012775 | -0.023859 | 0.022920 | -0.010805 | -0.007267 | -0.002023 | -0.004441 | 0.009557 | -0.030823 | 0.014757 | -0.020187 | -0.006023 | -0.005584 | 0.026076 | -0.015549 | -0.008683 | -0.016362 | 0.002207 | -0.023385 | 0.005334 | 0.003456 | 0.005356 | -0.004534 | 0.000739 | -0.006997 | 0.011008 | 0.002535 | 0.002298 | 0.003133 | -0.003178 | -0.002530 | 0.006550 | -0.000339 | -0.001555 | -0.000788 | -0.001337 | 0.004062 | 0.002284 | -0.000613 | 0.002491 | -0.000634 | -0.001495 | 0.001486 | -0.001734 | -0.006943 | -0.002032 | -0.001959 | 0.002479 | 0.003926 | 0.003850 | -0.001939 | 0.000750 | -0.009864 | 0.003988 | 0.004844 | 0.002949 | 0.005727 | -0.009374 | 0.001796 | -0.002874 | 0.004846 | 0.005252 | -0.004622 | -0.003375 | 0.001232 | 0.001901 |
| IC7 | 0.945002 | 0.106196 | 0.061762 | 0.200184 | 0.115942 | -0.087196 | -0.066619 | -0.047573 | -0.053247 | 0.021240 | -0.013440 | 0.046005 | 0.010834 | 0.040779 | 0.002376 | 0.009920 | 0.019712 | -0.020408 | -0.009777 | 0.003411 | -0.010892 | -0.009547 | 0.014334 | -0.018311 | 0.035862 | -0.006259 | -0.016587 | 0.009516 | -0.007031 | -0.025579 | 0.011860 | -0.015003 | 0.004999 | -0.016622 | 0.007862 | -0.010240 | 0.003725 | -0.010285 | 0.000941 | -0.007875 | -0.016994 | 0.007604 | 0.002392 | 0.012955 | 0.028767 | 0.001492 | -0.009809 | 0.020581 | 0.018622 | -0.000687 | -0.007678 | 0.012139 | -0.009983 | -0.008221 | 0.039319 | -0.002538 | 0.028117 | -0.000788 | -0.006479 | -0.000265 | 0.002883 | 0.006139 | 0.030699 | -0.001938 | -0.013144 | -0.012830 | -0.024212 | 0.046602 | -0.011392 | 0.009784 | -0.009703 | -0.007323 | 0.014129 | -0.000046 | 0.000604 | -0.003899 |
| IC8 | 0.653262 | 0.275477 | -0.083420 | 0.518374 | 0.253361 | -0.120614 | -0.103212 | 0.132169 | -0.041008 | 0.114442 | 0.003473 | 0.080627 | -0.021176 | 0.063747 | 0.022296 | 0.002996 | 0.061392 | -0.026466 | 0.043280 | -0.023107 | 0.008604 | -0.004127 | 0.053125 | -0.085550 | 0.134666 | -0.007724 | 0.049520 | 0.026195 | 0.066198 | 0.006037 | 0.040196 | -0.030612 | 0.045585 | -0.032974 | 0.011809 | -0.071789 | 0.033630 | 0.040557 | 0.007680 | 0.051066 | 0.094916 | -0.100718 | -0.004198 | -0.029244 | -0.048981 | -0.017650 | 0.008640 | -0.028142 | -0.028116 | -0.000999 | 0.011564 | -0.004475 | 0.013392 | 0.012328 | -0.032171 | -0.005175 | -0.023619 | -0.006846 | 0.003089 | -0.005446 | 0.001454 | -0.000883 | -0.015520 | -0.009957 | 0.005985 | 0.003902 | 0.008469 | -0.024011 | 0.001501 | -0.009072 | 0.004779 | 0.011391 | -0.005215 | 0.007224 | -0.002490 | 0.003474 |
| IC9 | -0.649612 | 0.341240 | -0.230208 | 0.428684 | 0.240583 | -0.054485 | -0.016039 | 0.283013 | 0.038394 | 0.124634 | 0.058653 | -0.032947 | -0.083295 | -0.020753 | 0.021386 | -0.001334 | -0.000080 | 0.001144 | 0.051860 | -0.020263 | 0.032039 | 0.017632 | 0.017648 | -0.041593 | 0.002284 | 0.022700 | 0.082159 | -0.034745 | 0.041801 | 0.083427 | -0.068408 | 0.039223 | -0.003710 | 0.077955 | -0.020110 | 0.021944 | -0.023030 | 0.004897 | 0.016077 | -0.010997 | -0.044333 | 0.082866 | 0.008419 | -0.016933 | 0.015107 | 0.032195 | 0.011664 | -0.002308 | 0.000666 | -0.016792 | 0.020623 | 0.000520 | 0.005136 | 0.023524 | -0.010582 | -0.013975 | -0.016669 | -0.018043 | 0.016309 | -0.027023 | -0.002109 | 0.007018 | -0.010919 | -0.000907 | -0.007313 | -0.006299 | -0.002284 | -0.019554 | 0.000533 | -0.010112 | 0.002485 | 0.004178 | 0.007398 | 0.018376 | -0.004801 | 0.023937 |
| IC10 | -0.976661 | 0.034894 | -0.103657 | 0.033571 | 0.053112 | -0.008499 | 0.043225 | 0.094762 | 0.025463 | 0.031232 | 0.039350 | -0.054000 | -0.033193 | -0.040176 | 0.000191 | 0.001356 | -0.019722 | 0.002835 | 0.000952 | 0.002629 | 0.013720 | 0.011643 | -0.034330 | 0.036245 | -0.042505 | 0.001948 | -0.001636 | -0.015527 | 0.002042 | -0.010096 | -0.010637 | 0.008505 | -0.003565 | 0.002725 | 0.009350 | 0.005108 | 0.001341 | -0.000669 | -0.004318 | -0.000530 | -0.003459 | -0.020377 | 0.001041 | 0.012186 | -0.005311 | -0.008739 | -0.001275 | -0.004646 | -0.002819 | 0.005401 | -0.010319 | -0.008166 | 0.004686 | -0.001948 | -0.003918 | 0.009690 | 0.002185 | 0.007820 | -0.012644 | 0.012630 | 0.004167 | -0.009915 | 0.000059 | 0.001230 | 0.007888 | 0.005755 | 0.002552 | 0.000132 | 0.002697 | 0.006670 | -0.005508 | -0.011376 | -0.007542 | -0.020187 | 0.006230 | -0.024900 |
| IC11 | -0.968000 | -0.148878 | 0.030744 | -0.157299 | -0.027238 | 0.015096 | 0.026135 | -0.029044 | 0.018379 | -0.009094 | 0.009158 | -0.023247 | 0.008791 | -0.021323 | -0.005803 | 0.001644 | -0.014735 | -0.001257 | -0.010105 | 0.005781 | 0.009984 | 0.002347 | -0.029446 | 0.037781 | -0.034056 | -0.002430 | -0.029496 | 0.000534 | -0.000703 | -0.031319 | 0.009364 | -0.005291 | -0.001452 | -0.009397 | 0.016024 | -0.003009 | 0.000536 | 0.000034 | -0.012675 | 0.004445 | 0.002716 | -0.014148 | 0.004614 | 0.007468 | -0.001219 | -0.003126 | -0.001551 | -0.003075 | 0.000623 | 0.001444 | -0.003104 | -0.005282 | -0.001744 | -0.000453 | -0.000258 | 0.000271 | -0.006075 | 0.000537 | -0.006357 | -0.003759 | -0.000140 | -0.001705 | -0.002710 | -0.004849 | -0.004905 | 0.001486 | -0.003010 | 0.004338 | 0.000516 | -0.004546 | -0.004062 | 0.003999 | 0.007094 | 0.012520 | -0.004814 | 0.016477 |
| IC12 | -0.906949 | -0.247403 | 0.153806 | -0.238940 | -0.075666 | 0.030979 | 0.002254 | -0.113432 | 0.017911 | -0.049460 | -0.030023 | 0.013447 | 0.034219 | 0.006549 | -0.009563 | 0.004229 | -0.006817 | -0.002002 | -0.002619 | 0.002828 | 0.006584 | -0.005459 | -0.006548 | 0.002600 | -0.013759 | 0.000960 | -0.024021 | 0.014967 | -0.000845 | -0.022091 | 0.019920 | -0.012192 | -0.005988 | -0.014084 | 0.008730 | -0.006253 | -0.005400 | -0.000941 | -0.010712 | 0.005939 | 0.004643 | 0.000876 | 0.002081 | -0.003151 | 0.003042 | 0.003190 | -0.004115 | 0.000522 | 0.000398 | 0.001521 | 0.002925 | 0.000313 | -0.004282 | -0.003152 | 0.001090 | -0.000878 | -0.010183 | -0.004070 | 0.005791 | -0.011601 | -0.006571 | 0.003869 | 0.000296 | -0.003008 | -0.009541 | -0.002225 | -0.006703 | 0.001095 | 0.000665 | -0.004772 | 0.009774 | 0.008963 | 0.010822 | 0.033701 | -0.014812 | 0.032282 |
| IC13 | -0.861020 | -0.277502 | 0.205181 | -0.270188 | -0.087599 | 0.051822 | -0.005132 | -0.150013 | 0.019745 | -0.069782 | -0.052966 | 0.042208 | 0.042208 | 0.024107 | -0.015655 | 0.007587 | 0.006017 | 0.002551 | 0.003334 | -0.004842 | 0.002320 | -0.004560 | 0.018976 | -0.029237 | 0.003485 | 0.007235 | -0.016220 | 0.022175 | 0.001201 | -0.013775 | 0.025903 | -0.019955 | -0.013716 | -0.017978 | -0.002020 | -0.008516 | -0.017769 | -0.010924 | -0.011755 | 0.008188 | 0.004443 | 0.026326 | -0.000263 | -0.007384 | -0.002589 | 0.013561 | -0.011440 | 0.002451 | 0.017061 | -0.007820 | 0.026723 | 0.020929 | -0.030728 | -0.005730 | 0.004789 | 0.000482 | -0.024833 | -0.004470 | 0.031049 | -0.033183 | -0.027771 | 0.008125 | 0.009587 | -0.006031 | -0.007345 | -0.050514 | 0.030216 | -0.028680 | 0.002358 | -0.021693 | -0.024307 | 0.007116 | 0.013141 | -0.046155 | 0.013439 | -0.010139 |
| IC14 | -0.775655 | -0.317981 | 0.306768 | -0.305316 | -0.109597 | 0.064138 | -0.019022 | -0.206274 | 0.018958 | -0.102823 | -0.078738 | 0.089061 | 0.037354 | 0.063699 | -0.015010 | 0.014659 | 0.016338 | 0.009608 | 0.026510 | -0.014324 | -0.010119 | -0.009059 | 0.054057 | -0.070919 | 0.019372 | 0.021164 | 0.029488 | 0.017071 | 0.008240 | 0.029310 | -0.007775 | 0.000666 | -0.015608 | -0.002772 | -0.024727 | 0.006711 | -0.009611 | -0.026962 | 0.007858 | -0.011112 | 0.001411 | 0.012081 | -0.019279 | -0.009536 | -0.005457 | -0.000844 | -0.005469 | -0.002952 | -0.003679 | 0.001977 | -0.001345 | 0.006345 | 0.003703 | -0.005382 | 0.003248 | 0.006945 | 0.021753 | 0.004208 | -0.002543 | 0.019675 | 0.011836 | -0.000557 | 0.010629 | 0.006923 | 0.007685 | 0.019111 | 0.002544 | -0.000580 | 0.000730 | 0.014503 | 0.014819 | -0.009474 | -0.017342 | 0.006499 | -0.000268 | -0.020116 |
| IC15 | 0.947807 | 0.153608 | -0.120186 | -0.116201 | 0.033191 | -0.059338 | 0.017778 | -0.183094 | -0.026048 | -0.044890 | -0.038487 | -0.003467 | 0.013322 | -0.006612 | -0.005875 | -0.006866 | -0.008344 | -0.002514 | -0.032352 | 0.026447 | -0.027197 | 0.000133 | -0.007994 | 0.028559 | -0.013861 | -0.001108 | -0.020188 | 0.007788 | -0.014864 | 0.003756 | 0.007170 | 0.008043 | 0.005006 | 0.008067 | -0.012331 | 0.011063 | 0.007949 | 0.006389 | 0.002829 | -0.003630 | -0.010366 | 0.002812 | 0.001249 | 0.002055 | 0.003550 | -0.002751 | 0.005212 | 0.006827 | 0.005863 | 0.003078 | -0.001312 | -0.005559 | -0.000123 | 0.001175 | -0.010015 | -0.003394 | -0.002522 | 0.004279 | 0.000757 | 0.002038 | -0.002991 | -0.000624 | -0.011948 | 0.003730 | 0.003671 | 0.004421 | 0.005674 | -0.011188 | 0.004530 | -0.004342 | 0.007747 | 0.007398 | -0.006120 | -0.003397 | 0.003482 | 0.001091 |
| IC16 | 0.945039 | 0.213411 | 0.060958 | 0.115958 | 0.075956 | -0.107533 | -0.055130 | -0.053011 | -0.052343 | 0.005263 | -0.020961 | 0.031446 | 0.023628 | 0.035453 | -0.003112 | 0.011713 | 0.013719 | -0.021439 | -0.007741 | 0.002528 | -0.014243 | -0.015187 | 0.011108 | -0.007043 | 0.028889 | -0.013856 | -0.021509 | 0.009479 | -0.013324 | -0.023036 | 0.016057 | -0.013364 | 0.005430 | -0.016446 | 0.006832 | -0.004486 | 0.003281 | -0.010472 | -0.003393 | -0.007929 | -0.017056 | 0.009434 | 0.000992 | 0.015570 | 0.028962 | 0.001489 | -0.009158 | 0.020657 | 0.017543 | 0.001620 | -0.005201 | 0.011689 | -0.009764 | -0.009655 | 0.035336 | -0.003374 | 0.024615 | 0.000753 | -0.003891 | 0.000842 | 0.002900 | 0.005679 | 0.027609 | 0.000494 | -0.011903 | -0.009495 | -0.022962 | 0.041362 | -0.012721 | 0.010421 | -0.009772 | -0.008120 | 0.015342 | -0.002614 | 0.000405 | -0.004675 |
| IC17 | 0.788243 | 0.335944 | 0.038351 | 0.358928 | 0.202136 | -0.093174 | -0.090409 | 0.098322 | -0.051568 | 0.067843 | 0.000426 | 0.047924 | 0.012611 | 0.044976 | 0.012592 | 0.006085 | 0.037736 | -0.024840 | 0.035567 | -0.024988 | 0.001356 | -0.009962 | 0.041579 | -0.061657 | 0.104961 | -0.018223 | 0.029719 | 0.022294 | 0.035211 | 0.005353 | 0.037521 | -0.030667 | 0.030806 | -0.035932 | 0.009272 | -0.050801 | 0.024571 | 0.030852 | 0.003190 | 0.038539 | 0.085076 | -0.082988 | -0.002516 | -0.027444 | -0.045054 | -0.012584 | 0.008051 | -0.024035 | -0.028168 | -0.001155 | 0.011977 | -0.000892 | 0.011924 | 0.005868 | -0.029139 | -0.005633 | -0.020933 | -0.006914 | 0.005374 | -0.001717 | 0.001792 | -0.000092 | -0.013743 | -0.007820 | 0.006480 | 0.003286 | 0.010578 | -0.023253 | 0.000023 | -0.007538 | 0.005018 | 0.009088 | -0.004208 | 0.002582 | -0.004924 | 0.004264 |
| IC18 | -0.343166 | 0.379658 | -0.126517 | 0.581996 | 0.353697 | -0.017086 | -0.045833 | 0.350923 | 0.033886 | 0.141185 | 0.093648 | -0.058580 | -0.081295 | -0.034100 | 0.021911 | -0.000340 | -0.003035 | 0.008437 | 0.055293 | -0.034038 | 0.037994 | 0.017822 | 0.025443 | -0.055824 | -0.000647 | 0.025071 | 0.096403 | -0.045105 | 0.034621 | 0.112372 | -0.095824 | 0.043465 | -0.018504 | 0.090353 | -0.030008 | 0.033124 | -0.038036 | 0.001993 | 0.024150 | -0.021938 | -0.054413 | 0.117453 | 0.009773 | -0.030963 | 0.018598 | 0.046351 | 0.014754 | -0.005143 | -0.003897 | -0.022053 | 0.029558 | 0.008056 | 0.008029 | 0.026488 | -0.009866 | -0.020361 | -0.019719 | -0.025132 | 0.025791 | -0.033358 | -0.002093 | 0.013323 | -0.014537 | -0.003143 | -0.010518 | -0.012091 | -0.002453 | -0.023731 | -0.000010 | -0.014203 | 0.004119 | 0.007306 | 0.007834 | 0.026007 | -0.007854 | 0.039256 |
| IC19 | -0.966681 | -0.055072 | -0.069611 | 0.083242 | 0.086564 | 0.017608 | 0.040753 | 0.104672 | 0.033046 | 0.039700 | 0.058590 | -0.069020 | -0.040218 | -0.049169 | 0.001790 | 0.000768 | -0.017835 | 0.012599 | -0.006773 | 0.004140 | 0.018164 | 0.013362 | -0.040150 | 0.042131 | -0.050173 | 0.002554 | -0.001326 | -0.018687 | -0.001758 | -0.013156 | -0.015728 | 0.009508 | -0.007169 | 0.000756 | 0.013343 | 0.004292 | 0.000622 | -0.002595 | -0.002354 | -0.001702 | -0.001003 | -0.023193 | -0.000888 | 0.012295 | -0.007851 | -0.011895 | -0.001608 | -0.006883 | -0.004513 | 0.006353 | -0.014417 | -0.008449 | 0.006577 | -0.003053 | -0.003364 | 0.013532 | 0.004397 | 0.008604 | -0.014513 | 0.016603 | 0.004726 | -0.011604 | 0.000843 | 0.001614 | 0.010492 | 0.005729 | 0.004050 | 0.001552 | 0.003291 | 0.008232 | -0.007146 | -0.013561 | -0.010743 | -0.023925 | 0.007573 | -0.030809 |
| IC20 | -0.949024 | -0.242338 | 0.058400 | -0.135097 | -0.018299 | 0.031684 | 0.021675 | -0.037907 | 0.023889 | -0.005042 | 0.019742 | -0.027080 | 0.004323 | -0.023951 | -0.004122 | 0.000543 | -0.009834 | 0.005447 | -0.014566 | 0.007187 | 0.012773 | 0.003351 | -0.031045 | 0.041188 | -0.036632 | -0.002175 | -0.028764 | -0.001266 | -0.001258 | -0.034576 | 0.008434 | -0.003501 | -0.002193 | -0.010287 | 0.019778 | -0.005889 | 0.000594 | 0.000801 | -0.012009 | 0.005806 | 0.004511 | -0.014219 | 0.004779 | 0.007331 | -0.001924 | -0.003295 | -0.001674 | -0.004395 | -0.000444 | 0.000791 | -0.005155 | -0.006101 | -0.001589 | 0.000266 | 0.000770 | 0.000978 | -0.005772 | 0.000250 | -0.007044 | -0.004640 | -0.000411 | -0.001947 | -0.003259 | -0.004543 | -0.004848 | 0.000918 | -0.003241 | 0.005842 | 0.000419 | -0.005483 | -0.005309 | 0.005145 | 0.007061 | 0.015044 | -0.004733 | 0.018336 |
| IC21 | -0.877152 | -0.330537 | 0.176582 | -0.221742 | -0.073152 | 0.046836 | -0.004705 | -0.127091 | 0.023154 | -0.048067 | -0.023192 | 0.013218 | 0.028358 | 0.008165 | -0.007867 | 0.003921 | -0.001695 | 0.005404 | -0.005785 | 0.002805 | 0.008690 | -0.005848 | -0.005698 | 0.002281 | -0.014277 | 0.001367 | -0.020782 | 0.012134 | 0.000177 | -0.022979 | 0.021099 | -0.010766 | -0.007544 | -0.013943 | 0.011289 | -0.008287 | -0.005396 | -0.000110 | -0.009755 | 0.008396 | 0.005549 | 0.001500 | 0.003149 | -0.002961 | 0.002600 | 0.002761 | -0.004429 | -0.000277 | -0.000291 | 0.000598 | 0.002089 | -0.000182 | -0.004995 | -0.003447 | 0.002077 | -0.000667 | -0.010859 | -0.004518 | 0.006538 | -0.012734 | -0.007274 | 0.004203 | 0.000093 | -0.001996 | -0.008942 | -0.002342 | -0.007494 | 0.000811 | 0.000515 | -0.005346 | 0.010040 | 0.009652 | 0.012365 | 0.037791 | -0.016463 | 0.034898 |
| IC22 | -0.825013 | -0.359452 | 0.227255 | -0.252293 | -0.087909 | 0.063163 | -0.013490 | -0.163203 | 0.025665 | -0.067142 | -0.049961 | 0.041870 | 0.037537 | 0.026753 | -0.012293 | 0.006731 | 0.010899 | 0.009459 | 0.001570 | -0.006412 | 0.003027 | -0.004946 | 0.021213 | -0.031673 | 0.004349 | 0.006237 | -0.010299 | 0.019317 | 0.003894 | -0.013276 | 0.026811 | -0.017589 | -0.016741 | -0.016704 | -0.001292 | -0.010885 | -0.017532 | -0.010540 | -0.010833 | 0.011350 | 0.005369 | 0.029528 | -0.000302 | -0.008228 | -0.004265 | 0.014004 | -0.011565 | 0.001563 | 0.017844 | -0.009530 | 0.028231 | 0.022493 | -0.033030 | -0.005136 | 0.004729 | 0.001400 | -0.026576 | -0.004379 | 0.034491 | -0.036618 | -0.030019 | 0.008797 | 0.009534 | -0.006245 | -0.006262 | -0.053909 | 0.033003 | -0.030155 | 0.002631 | -0.023874 | -0.027056 | 0.007719 | 0.015240 | -0.051932 | 0.014483 | -0.012077 |
| IC23 | -0.736689 | -0.396682 | 0.316921 | -0.289413 | -0.108127 | 0.073553 | -0.029865 | -0.215992 | 0.025687 | -0.098767 | -0.074641 | 0.087968 | 0.030880 | 0.066741 | -0.012672 | 0.014202 | 0.020184 | 0.017547 | 0.026502 | -0.017014 | -0.009809 | -0.010554 | 0.057067 | -0.072135 | 0.019681 | 0.019656 | 0.036573 | 0.011167 | 0.011160 | 0.031764 | -0.007602 | 0.003476 | -0.017601 | -0.000193 | -0.024450 | 0.007373 | -0.007672 | -0.026232 | 0.010197 | -0.006340 | 0.000106 | 0.012925 | -0.017837 | -0.008031 | -0.007959 | -0.002487 | -0.005137 | -0.003528 | -0.006063 | 0.002059 | -0.002864 | 0.004577 | 0.005166 | -0.004627 | 0.004837 | 0.007735 | 0.022655 | 0.005212 | -0.003131 | 0.021971 | 0.012187 | -0.000204 | 0.009910 | 0.007934 | 0.009584 | 0.021539 | 0.002094 | 0.000601 | 0.000340 | 0.016342 | 0.014894 | -0.010014 | -0.016948 | 0.006560 | -0.000278 | -0.021315 |
| HHAS1 | 0.598598 | -0.070289 | 0.760290 | -0.107771 | 0.139574 | -0.145607 | 0.019402 | 0.038151 | -0.012343 | -0.013365 | -0.001599 | -0.037940 | 0.001823 | 0.008182 | 0.003772 | 0.009327 | -0.002859 | -0.013851 | -0.000914 | 0.007312 | 0.004032 | 0.010884 | 0.000495 | 0.006744 | 0.008025 | -0.003590 | 0.014071 | -0.012180 | -0.017413 | 0.002854 | 0.005989 | -0.002710 | -0.013853 | -0.007728 | 0.004838 | 0.002015 | 0.000621 | -0.004950 | 0.000854 | -0.003794 | -0.000269 | -0.003093 | -0.001529 | 0.003165 | 0.005742 | -0.001582 | 0.000946 | 0.000069 | 0.000172 | -0.001332 | 0.001474 | -0.002603 | 0.000050 | -0.001826 | 0.002208 | 0.001608 | -0.006065 | 0.001437 | -0.001656 | -0.002918 | 0.000707 | -0.000031 | -0.003323 | 0.002036 | 0.002444 | 0.000794 | 0.001419 | -0.001317 | -0.001191 | -0.003642 | -0.000080 | -0.004204 | 0.001226 | -0.001079 | 0.003472 | 0.000298 |
| HHAS2 | 0.848349 | 0.135761 | -0.315831 | -0.311706 | 0.104287 | -0.098535 | 0.062648 | -0.142958 | -0.008215 | -0.025081 | -0.053789 | -0.031380 | 0.008540 | -0.028050 | -0.000070 | -0.018084 | -0.040479 | 0.014277 | -0.013045 | 0.034089 | -0.004008 | 0.046573 | -0.008626 | 0.021485 | -0.016697 | 0.012889 | -0.015295 | 0.003463 | -0.005179 | 0.016451 | 0.007601 | 0.009549 | 0.002109 | 0.020022 | -0.014422 | 0.011312 | 0.023062 | 0.002688 | 0.009369 | 0.001227 | -0.005015 | -0.001664 | -0.003567 | -0.001320 | -0.002333 | -0.005001 | 0.010077 | 0.001792 | 0.002152 | -0.012766 | 0.004532 | -0.004654 | -0.003813 | 0.001160 | -0.003715 | 0.003252 | -0.001582 | 0.004745 | -0.003775 | -0.001317 | -0.006587 | -0.001121 | -0.006894 | -0.005639 | 0.007649 | 0.002710 | 0.009873 | -0.014313 | 0.007116 | -0.005972 | 0.009769 | 0.003393 | -0.006614 | -0.004826 | 0.002869 | 0.001180 |
| HHAS3 | -0.816408 | -0.257210 | 0.491345 | 0.036286 | 0.084119 | 0.072627 | -0.041786 | 0.042187 | -0.044428 | -0.003269 | 0.018405 | -0.025449 | -0.023493 | 0.032980 | -0.009482 | 0.004112 | -0.024986 | -0.018591 | -0.007370 | 0.011385 | 0.002504 | 0.023108 | -0.001686 | -0.002493 | -0.007781 | 0.005882 | 0.006425 | -0.008958 | 0.006731 | -0.007117 | 0.007406 | 0.005648 | -0.005647 | 0.000824 | -0.003244 | -0.002044 | -0.007518 | -0.002921 | -0.006492 | -0.000066 | 0.006584 | -0.006310 | 0.007717 | 0.004365 | -0.001146 | -0.002547 | -0.005662 | -0.003223 | 0.009373 | -0.002084 | 0.006141 | -0.001697 | -0.000430 | 0.006025 | 0.001559 | 0.004014 | -0.005014 | -0.003930 | -0.000276 | -0.006875 | 0.001775 | -0.002641 | 0.003982 | -0.002132 | 0.000783 | 0.001609 | -0.004933 | 0.004626 | 0.000997 | -0.000538 | 0.002757 | -0.001542 | -0.000944 | -0.000161 | 0.001439 | 0.000653 |
| HHAS4 | 0.914732 | 0.091292 | -0.243205 | -0.179468 | 0.037324 | -0.036610 | 0.025920 | -0.215510 | -0.044530 | -0.054584 | -0.023526 | -0.007545 | -0.001464 | -0.022457 | -0.002745 | 0.004018 | -0.008084 | -0.007974 | -0.030101 | 0.034278 | -0.030247 | 0.005727 | -0.012492 | 0.031162 | -0.010770 | 0.002219 | -0.009972 | 0.002555 | -0.013809 | 0.007323 | 0.006317 | 0.013179 | -0.000041 | 0.008042 | -0.016704 | 0.009289 | 0.003044 | 0.008419 | 0.002732 | -0.003766 | -0.006056 | 0.006066 | 0.002419 | -0.001046 | -0.002583 | -0.003183 | 0.003503 | 0.004254 | 0.004690 | 0.001840 | 0.000213 | -0.006179 | 0.002353 | 0.000716 | -0.007554 | -0.001258 | -0.004299 | 0.003425 | 0.002563 | 0.000978 | -0.002344 | -0.000783 | -0.014561 | 0.004789 | 0.006856 | 0.002986 | 0.005065 | -0.009025 | 0.004728 | -0.003125 | 0.008297 | 0.006380 | -0.005057 | -0.003143 | 0.004299 | 0.000815 |
| MC1 | -0.194943 | -0.579454 | -0.472986 | 0.509353 | -0.070167 | -0.230396 | 0.065604 | -0.171916 | -0.116905 | -0.104469 | -0.050397 | -0.078487 | 0.027065 | -0.023265 | -0.028670 | 0.022264 | -0.032088 | -0.054279 | 0.007257 | -0.026977 | 0.012679 | 0.010448 | -0.041058 | -0.005086 | 0.012197 | -0.012894 | -0.002752 | 0.038657 | 0.004857 | 0.032349 | 0.007686 | 0.005545 | 0.012274 | -0.014761 | 0.004802 | -0.002772 | 0.011742 | -0.010349 | 0.009023 | 0.004767 | 0.009542 | 0.010798 | 0.003961 | -0.000647 | 0.005235 | 0.010739 | -0.011473 | -0.000125 | -0.004708 | -0.008949 | -0.004258 | -0.000121 | -0.013411 | 0.006348 | 0.007791 | 0.003276 | 0.012639 | -0.010247 | 0.001868 | 0.002490 | -0.003880 | 0.001173 | 0.006450 | -0.006997 | -0.000525 | -0.000854 | -0.000241 | -0.001108 | 0.015855 | -0.004650 | 0.004535 | -0.018557 | -0.003046 | -0.001245 | 0.002146 | 0.001372 |
| MC2 | 0.078584 | 0.653114 | 0.501010 | -0.358073 | 0.349506 | 0.112888 | -0.104763 | 0.029871 | 0.095145 | 0.104245 | 0.044160 | 0.060937 | -0.024398 | 0.023818 | 0.022586 | -0.008605 | 0.034189 | 0.047761 | -0.015343 | 0.031831 | -0.014058 | -0.011559 | 0.036812 | 0.009371 | -0.017718 | 0.011555 | 0.003186 | -0.033421 | 0.000924 | -0.026175 | -0.008184 | -0.002135 | -0.014006 | 0.016066 | -0.003153 | 0.000095 | -0.009675 | 0.009953 | -0.006901 | -0.001457 | -0.010538 | -0.010965 | -0.002989 | -0.000081 | -0.003724 | -0.009970 | 0.011238 | 0.000302 | 0.005576 | 0.009364 | 0.003866 | -0.000307 | 0.013579 | -0.005216 | -0.008095 | -0.004189 | -0.011367 | 0.009491 | -0.002006 | -0.002285 | 0.004078 | -0.001066 | -0.006068 | 0.006377 | 0.000897 | 0.000148 | -0.001457 | 0.000469 | -0.015286 | 0.003409 | -0.003891 | 0.017617 | 0.003011 | 0.000556 | -0.002189 | -0.002175 |
| MC3 | -0.284115 | -0.607538 | -0.175100 | 0.491775 | -0.232075 | -0.270179 | 0.192768 | -0.123105 | -0.178896 | -0.050939 | 0.009536 | 0.046650 | 0.009219 | 0.117638 | -0.059509 | 0.049235 | -0.021926 | -0.119122 | 0.011181 | -0.054021 | -0.030288 | 0.030861 | -0.032885 | 0.031834 | -0.010794 | -0.045524 | -0.003552 | -0.008118 | 0.021870 | 0.052793 | 0.006932 | 0.011429 | 0.012018 | -0.036860 | 0.049775 | -0.005895 | -0.003727 | 0.012940 | -0.015334 | -0.009690 | -0.005913 | -0.000030 | 0.018375 | 0.000948 | 0.003366 | 0.010337 | -0.006784 | -0.004234 | 0.002104 | -0.008550 | 0.008127 | 0.008227 | -0.006341 | 0.009236 | 0.016691 | -0.007310 | -0.004303 | -0.005897 | 0.001759 | -0.019764 | -0.002522 | -0.010738 | -0.008352 | 0.001377 | -0.002011 | 0.005526 | -0.005418 | 0.003468 | 0.014619 | 0.000743 | 0.005168 | -0.016863 | 0.003058 | 0.011205 | 0.016443 | -0.006318 |
| TPE1 | -0.722568 | 0.268223 | 0.312502 | 0.363072 | 0.334526 | -0.065761 | 0.084956 | -0.029031 | 0.017553 | -0.087905 | 0.023823 | 0.057565 | 0.083637 | -0.066042 | 0.016590 | -0.027727 | 0.051494 | 0.026740 | 0.009242 | 0.069330 | 0.012171 | 0.024158 | 0.036564 | 0.024444 | -0.003308 | 0.029350 | -0.014841 | 0.058093 | -0.018695 | -0.007099 | -0.051535 | -0.000598 | -0.002382 | 0.014502 | 0.018862 | -0.032794 | 0.026289 | 0.007827 | 0.012511 | -0.004004 | -0.003502 | -0.007655 | -0.014543 | 0.012560 | 0.000482 | 0.004756 | -0.008224 | 0.005847 | -0.003841 | -0.002373 | 0.006385 | 0.004495 | 0.004187 | 0.005239 | 0.013574 | -0.000429 | 0.007611 | -0.008425 | 0.006880 | -0.003928 | 0.006573 | 0.024418 | -0.013750 | 0.016094 | 0.015530 | -0.007778 | 0.003063 | 0.001726 | -0.018918 | -0.003184 | -0.009292 | 0.005775 | 0.003415 | 0.000039 | -0.004122 | -0.003124 |
| TPE2 | 0.693486 | 0.458827 | -0.377635 | -0.115878 | 0.049763 | -0.267266 | -0.003172 | -0.097065 | 0.012857 | 0.044320 | -0.010869 | -0.036278 | 0.036104 | -0.003951 | -0.001573 | 0.041265 | 0.054360 | -0.008265 | -0.032279 | -0.051171 | 0.053091 | -0.025179 | -0.013034 | -0.003163 | -0.000032 | -0.026690 | 0.044493 | -0.008052 | 0.016002 | -0.027730 | 0.055425 | 0.023589 | 0.005506 | -0.039974 | -0.016715 | 0.041873 | -0.070716 | 0.012161 | -0.006423 | -0.024763 | -0.004101 | 0.013317 | -0.002381 | -0.046318 | 0.001835 | 0.005943 | 0.022401 | -0.020937 | -0.007983 | 0.010762 | -0.046709 | 0.006992 | -0.011494 | -0.008754 | -0.015479 | -0.013998 | -0.012076 | 0.036756 | -0.016575 | -0.004599 | -0.013033 | -0.029003 | 0.034850 | -0.026464 | -0.013223 | 0.008584 | -0.020403 | -0.003453 | 0.050022 | -0.010956 | 0.010340 | -0.006393 | -0.022786 | 0.008496 | 0.050286 | 0.015270 |
| TPE3 | 0.235548 | -0.663192 | -0.436966 | -0.340996 | 0.185688 | 0.001694 | -0.005274 | -0.015074 | 0.164982 | 0.136938 | -0.024758 | -0.076151 | -0.152723 | 0.118253 | -0.032631 | 0.042412 | -0.091124 | -0.015111 | -0.115452 | -0.117720 | -0.057961 | -0.008309 | -0.040752 | -0.060816 | 0.009309 | -0.052740 | -0.009256 | -0.076252 | 0.023219 | 0.029542 | 0.030017 | -0.021414 | 0.013207 | 0.014967 | -0.034828 | -0.033044 | 0.034863 | 0.001725 | -0.006168 | 0.038208 | -0.021588 | 0.011107 | 0.007154 | 0.023505 | 0.006755 | -0.015893 | -0.008873 | 0.006601 | 0.022630 | -0.000006 | 0.022745 | 0.005551 | -0.006694 | -0.002799 | -0.005662 | 0.007374 | -0.005103 | 0.001376 | -0.001032 | 0.020171 | -0.003309 | -0.007743 | 0.004828 | -0.004436 | -0.006722 | -0.011575 | 0.007309 | 0.009749 | -0.003147 | 0.031961 | 0.004051 | 0.005221 | 0.001059 | -0.005598 | -0.024875 | 0.000026 |
| TPE4 | 0.363960 | -0.606867 | -0.483862 | -0.321159 | 0.184960 | -0.027313 | 0.007110 | -0.033526 | 0.107665 | 0.145208 | -0.015362 | -0.051479 | -0.126140 | 0.091018 | -0.027309 | 0.013583 | -0.068842 | -0.031382 | -0.080947 | -0.116404 | -0.069050 | 0.029277 | -0.027790 | -0.055415 | 0.003077 | -0.052842 | -0.011424 | -0.055778 | 0.006764 | 0.024508 | 0.001846 | 0.004642 | -0.011813 | 0.003473 | -0.040353 | -0.024752 | 0.021272 | 0.020397 | -0.011705 | 0.033591 | -0.001534 | 0.002609 | 0.028318 | 0.027068 | 0.024614 | -0.007955 | -0.002121 | 0.015677 | 0.019436 | -0.005192 | 0.017780 | 0.004665 | -0.014327 | -0.002755 | -0.017555 | 0.003497 | -0.014127 | -0.005438 | -0.001432 | 0.012604 | -0.008256 | -0.017918 | 0.034805 | -0.017147 | -0.002953 | 0.004942 | 0.011025 | 0.006823 | -0.000192 | 0.043737 | -0.000878 | 0.005477 | -0.000873 | -0.017092 | -0.022551 | -0.007135 |
| TPE5 | -0.296712 | -0.584458 | -0.158843 | -0.299326 | 0.144564 | 0.071688 | -0.062418 | 0.083421 | 0.297174 | 0.062286 | -0.028504 | -0.135434 | -0.192566 | 0.161592 | -0.037925 | 0.130255 | -0.124283 | 0.034417 | -0.197553 | -0.068423 | -0.004411 | -0.120999 | -0.077989 | -0.054853 | 0.048167 | -0.018682 | -0.012136 | -0.089326 | 0.051647 | 0.015022 | 0.079619 | -0.094236 | 0.078715 | 0.031250 | 0.020843 | -0.069528 | 0.073389 | -0.039775 | 0.010351 | 0.004741 | -0.061871 | 0.045876 | -0.093911 | -0.036220 | -0.021167 | -0.006385 | -0.000914 | -0.019172 | 0.040697 | -0.015953 | 0.073784 | 0.011817 | 0.006025 | -0.023078 | -0.004232 | 0.026595 | 0.028677 | 0.021950 | -0.015965 | 0.037582 | -0.015455 | -0.045194 | -0.085647 | 0.051093 | -0.007368 | -0.051563 | -0.002948 | 0.034793 | -0.017250 | -0.012305 | 0.026471 | 0.001386 | 0.004439 | 0.023265 | -0.046414 | 0.022095 |
| TPE6 | 0.236943 | -0.483986 | -0.077520 | -0.128667 | 0.010410 | 0.122097 | 0.074195 | -0.142292 | 0.079185 | 0.078729 | -0.107838 | -0.015056 | -0.058129 | 0.072563 | -0.051664 | -0.013489 | -0.082475 | 0.034325 | -0.027023 | -0.115898 | -0.015659 | -0.042940 | 0.014971 | -0.045165 | -0.092475 | -0.099545 | 0.053170 | -0.166656 | 0.092813 | 0.108760 | 0.162591 | -0.038740 | 0.063900 | 0.083125 | -0.131692 | 0.076782 | -0.006718 | -0.095390 | 0.015254 | 0.179918 | -0.096022 | -0.043855 | 0.133298 | 0.193577 | -0.148197 | -0.146441 | -0.129069 | -0.027694 | -0.058194 | 0.151647 | -0.182770 | -0.020998 | 0.065150 | 0.096168 | 0.178403 | -0.037208 | -0.011439 | 0.007065 | 0.074343 | 0.012471 | 0.132153 | 0.333810 | -0.043338 | -0.057179 | -0.047048 | -0.053628 | -0.017487 | -0.080181 | 0.023141 | -0.009504 | -0.032802 | 0.009884 | 0.010939 | 0.048137 | 0.088012 | 0.006057 |
| TPE7 | 0.048184 | -0.469942 | -0.270681 | 0.086456 | -0.055388 | -0.278427 | -0.049569 | 0.098935 | -0.279741 | 0.141197 | -0.143582 | 0.090676 | 0.053493 | -0.131779 | 0.001079 | 0.064817 | -0.036387 | 0.008827 | 0.030988 | -0.018564 | -0.014981 | 0.034142 | 0.031403 | 0.044963 | 0.075772 | -0.032980 | -0.032329 | -0.112658 | -0.036303 | 0.004365 | -0.008620 | -0.030125 | -0.013223 | -0.031237 | 0.017873 | 0.016283 | -0.049822 | -0.023304 | -0.081252 | 0.116230 | -0.049924 | 0.038557 | 0.120487 | 0.037853 | -0.114783 | 0.020990 | -0.149751 | -0.017288 | 0.056481 | 0.009496 | 0.129629 | -0.139145 | 0.223728 | -0.166568 | -0.110200 | -0.014252 | 0.287730 | -0.018911 | -0.175760 | -0.097070 | -0.195526 | 0.034493 | 0.073812 | 0.079815 | -0.076016 | 0.029351 | -0.013658 | -0.126177 | 0.030518 | -0.050960 | 0.003835 | 0.040541 | -0.010761 | 0.000216 | 0.017908 | -0.017276 |
| TPE8 | 0.767482 | -0.397887 | -0.022285 | -0.080062 | -0.018289 | 0.134189 | -0.221955 | -0.179949 | -0.229457 | 0.025993 | 0.030107 | -0.052601 | -0.049543 | 0.020267 | -0.027894 | 0.093237 | -0.116528 | -0.073764 | 0.025421 | 0.015125 | -0.021838 | -0.039885 | -0.018600 | 0.001854 | -0.074043 | -0.021260 | 0.003716 | -0.065924 | 0.031911 | 0.037671 | 0.047027 | -0.013841 | -0.045264 | 0.007928 | 0.031373 | 0.054466 | -0.022283 | -0.035442 | 0.002258 | 0.027940 | 0.037598 | 0.001398 | 0.020452 | 0.002497 | -0.008227 | -0.007693 | 0.000878 | -0.002076 | -0.007716 | -0.010863 | 0.006518 | -0.016841 | -0.007561 | 0.003162 | -0.020212 | -0.005029 | -0.021648 | -0.019169 | 0.011071 | -0.013684 | 0.016190 | -0.029573 | -0.011353 | -0.011354 | -0.019559 | 0.016450 | 0.003166 | -0.016828 | -0.001089 | -0.003427 | 0.005973 | -0.017670 | 0.014564 | 0.004801 | -0.031922 | -0.026396 |
| TPE9 | -0.134684 | 0.269793 | 0.621352 | -0.110288 | -0.261248 | 0.114726 | -0.421707 | -0.229782 | -0.165063 | 0.103247 | -0.108497 | -0.085206 | -0.169945 | 0.134683 | -0.012652 | -0.102597 | -0.011409 | 0.001429 | 0.159991 | 0.008388 | -0.061504 | -0.010008 | -0.071962 | 0.021235 | 0.064454 | 0.044972 | -0.006191 | -0.015622 | 0.009330 | 0.014218 | 0.007216 | 0.036987 | 0.026662 | -0.005208 | -0.035811 | 0.041486 | 0.005669 | -0.015609 | -0.026780 | -0.031208 | 0.006583 | -0.026421 | 0.032490 | -0.016823 | 0.012730 | 0.001321 | 0.029230 | 0.012039 | 0.010354 | 0.011210 | 0.008051 | -0.014838 | 0.015518 | 0.016508 | 0.012156 | 0.023357 | 0.003624 | -0.014214 | 0.003792 | 0.024487 | -0.000002 | -0.005402 | -0.009417 | -0.006737 | 0.002209 | 0.011654 | 0.002841 | 0.014942 | -0.017206 | -0.016640 | 0.010773 | -0.000215 | 0.014620 | -0.021972 | -0.001943 | 0.017128 |
| PEC1 | 0.181883 | 0.471754 | 0.245068 | 0.179377 | -0.007565 | 0.104852 | 0.071722 | -0.059660 | 0.108756 | -0.057039 | 0.019153 | 0.110513 | 0.054484 | 0.103948 | -0.057461 | 0.006646 | -0.055134 | -0.020328 | -0.016606 | -0.053041 | -0.115680 | 0.087215 | -0.052568 | -0.041698 | -0.038898 | -0.073249 | -0.002478 | 0.019383 | 0.028129 | 0.107376 | 0.060289 | 0.168782 | -0.067143 | -0.108475 | 0.287848 | 0.075347 | 0.053967 | 0.279513 | -0.001739 | -0.174300 | -0.170971 | -0.001415 | -0.064182 | 0.010475 | -0.124606 | -0.067582 | -0.010105 | -0.239375 | 0.048653 | 0.135686 | 0.015346 | 0.225983 | 0.101701 | 0.049200 | 0.129105 | 0.083927 | -0.047735 | -0.099226 | -0.016289 | -0.041097 | -0.055233 | -0.051890 | -0.023410 | -0.008055 | -0.086274 | 0.066774 | 0.058150 | 0.007973 | 0.038139 | -0.027413 | 0.047213 | 0.043016 | -0.011600 | 0.019123 | 0.023449 | -0.038796 |
| PEC2 | -0.445487 | 0.633158 | -0.010145 | 0.198655 | -0.093691 | -0.046933 | -0.066380 | -0.044165 | 0.381749 | 0.004680 | -0.012888 | -0.163710 | 0.016553 | -0.039582 | -0.017282 | 0.093160 | -0.034607 | 0.084122 | -0.044673 | -0.011221 | -0.011613 | -0.037567 | -0.071786 | 0.027970 | 0.042535 | -0.017578 | 0.066132 | 0.062224 | -0.038253 | -0.072011 | 0.029303 | -0.027415 | 0.030325 | 0.026545 | -0.106845 | 0.026647 | -0.075764 | -0.091995 | 0.001619 | -0.048796 | 0.066539 | -0.022370 | 0.038209 | 0.027562 | -0.032809 | 0.034559 | 0.018140 | 0.026256 | 0.002996 | -0.117342 | 0.008119 | -0.015662 | -0.003259 | 0.023248 | 0.018845 | -0.046224 | -0.016191 | 0.053111 | 0.000427 | -0.099773 | 0.036390 | -0.032764 | -0.007963 | -0.012409 | 0.021562 | 0.070174 | -0.017397 | 0.003395 | 0.011217 | -0.018603 | -0.014516 | 0.024346 | -0.011273 | 0.052144 | 0.030576 | -0.049394 |
| TPE10 | -0.691090 | 0.160528 | -0.403893 | -0.024623 | 0.048485 | -0.359143 | 0.043995 | -0.030785 | 0.357310 | 0.107843 | -0.039939 | -0.075836 | -0.088322 | -0.010982 | -0.011967 | 0.111429 | 0.000701 | 0.067895 | -0.066166 | -0.054996 | -0.053417 | 0.001955 | -0.007075 | 0.012545 | 0.030395 | -0.013759 | 0.028333 | 0.037950 | -0.034460 | -0.023517 | 0.025782 | 0.018166 | 0.015033 | -0.017027 | -0.019637 | 0.010412 | -0.014511 | 0.023136 | -0.005855 | -0.024546 | 0.010614 | 0.001693 | -0.003145 | -0.002201 | 0.004616 | 0.013276 | -0.002740 | -0.006952 | -0.004968 | -0.012514 | -0.018728 | 0.020552 | 0.003736 | -0.018055 | -0.006430 | -0.008566 | 0.000845 | -0.004963 | 0.002851 | -0.019731 | 0.003633 | 0.010755 | 0.014373 | -0.000332 | 0.008510 | 0.008663 | 0.004597 | 0.005623 | -0.000846 | -0.003157 | 0.002207 | 0.011218 | 0.000970 | 0.000975 | 0.007055 | -0.006843 |
| TPE11 | -0.636115 | 0.243959 | -0.340314 | -0.090060 | 0.023482 | -0.420358 | -0.028420 | -0.078062 | 0.352540 | 0.120347 | -0.072445 | -0.127445 | -0.100109 | -0.024428 | -0.001254 | 0.114063 | -0.040323 | 0.091637 | -0.072202 | -0.050570 | -0.036660 | -0.032090 | -0.036020 | 0.014831 | 0.044758 | -0.021072 | 0.049197 | 0.042957 | -0.033763 | -0.016671 | 0.042116 | -0.002262 | 0.040571 | -0.006877 | -0.021745 | 0.024877 | -0.022163 | 0.020829 | -0.015364 | -0.027098 | -0.000522 | -0.005347 | -0.005931 | -0.003771 | 0.007055 | 0.022030 | -0.001506 | -0.013491 | -0.011299 | -0.008049 | -0.024058 | 0.028027 | 0.012502 | -0.024060 | -0.005020 | -0.000395 | 0.006698 | -0.013098 | 0.006787 | -0.019582 | 0.006994 | 0.011936 | 0.019698 | -0.004624 | 0.006684 | 0.006665 | 0.009327 | 0.010207 | -0.004362 | -0.012533 | 0.003771 | 0.011117 | -0.004156 | -0.000388 | 0.003489 | 0.002231 |
| TPE12 | -0.250396 | 0.317833 | -0.255219 | -0.277209 | -0.193948 | -0.432097 | -0.079622 | -0.073294 | 0.272349 | 0.101338 | -0.147962 | -0.254258 | -0.114164 | -0.098073 | 0.027823 | 0.130920 | -0.188338 | 0.148652 | -0.140965 | -0.044629 | 0.028762 | -0.136218 | -0.113780 | -0.020240 | 0.065733 | -0.063732 | 0.128581 | 0.062689 | -0.049272 | -0.005092 | 0.094374 | -0.078763 | 0.115119 | 0.032698 | -0.031640 | 0.051786 | -0.039594 | 0.016385 | -0.028425 | -0.027168 | -0.022850 | -0.015041 | -0.029177 | -0.012317 | 0.008425 | 0.062796 | -0.012861 | -0.049844 | -0.041446 | 0.008615 | -0.056409 | 0.059503 | 0.044139 | -0.066779 | 0.003311 | 0.027044 | 0.034199 | -0.036984 | 0.018644 | -0.019306 | 0.016120 | 0.029995 | 0.044451 | -0.012315 | -0.004716 | -0.006905 | 0.032286 | 0.020276 | -0.026921 | -0.045663 | 0.001931 | 0.009384 | -0.023574 | -0.000993 | -0.019990 | 0.043168 |
| TPE13 | -0.729041 | 0.090224 | -0.372611 | 0.061524 | 0.144916 | -0.313434 | 0.060753 | -0.035562 | 0.324868 | 0.133360 | -0.012492 | 0.032125 | -0.081457 | 0.041810 | -0.020505 | 0.073354 | 0.101330 | 0.031451 | 0.002852 | -0.033457 | -0.093135 | 0.077231 | 0.035983 | 0.029659 | 0.025392 | 0.012213 | -0.022747 | 0.016133 | -0.014731 | -0.031724 | -0.014223 | 0.067878 | -0.024429 | -0.042995 | -0.010359 | -0.005519 | 0.002036 | 0.021248 | 0.002778 | -0.013699 | 0.019014 | 0.013957 | 0.008136 | 0.005932 | 0.009538 | -0.013037 | 0.009025 | 0.013443 | 0.015066 | -0.006318 | 0.002216 | -0.003312 | -0.011819 | 0.009071 | -0.013032 | -0.015399 | -0.012355 | 0.006560 | -0.002631 | -0.005370 | 0.000862 | 0.006605 | 0.001553 | -0.000130 | 0.007631 | 0.008812 | -0.008528 | -0.004511 | 0.007559 | 0.010950 | 0.001057 | 0.006621 | 0.009526 | 0.000891 | 0.017724 | -0.021062 |
| LFC1 | -0.708617 | 0.136540 | -0.552528 | 0.295810 | 0.215246 | 0.095527 | -0.106486 | -0.071355 | 0.036070 | 0.064202 | -0.012370 | 0.034097 | -0.004406 | 0.026186 | 0.007423 | -0.036532 | 0.039367 | -0.010787 | -0.001421 | -0.006741 | 0.024460 | -0.035268 | -0.007774 | 0.003628 | -0.014683 | -0.010779 | -0.012730 | -0.012297 | -0.002421 | -0.005488 | 0.004241 | 0.004494 | -0.005676 | 0.003045 | 0.002805 | 0.008226 | 0.001685 | -0.004021 | 0.005421 | 0.006854 | 0.002156 | 0.001816 | -0.002839 | -0.010342 | -0.005034 | 0.003528 | 0.002581 | -0.001902 | -0.003567 | -0.001050 | -0.003329 | 0.000135 | -0.003672 | -0.001169 | -0.000078 | 0.001618 | 0.004457 | -0.001065 | -0.001697 | 0.001181 | -0.001289 | -0.000319 | 0.002180 | -0.001512 | -0.005186 | -0.003209 | 0.001184 | -0.000435 | 0.005132 | 0.003190 | -0.003751 | 0.001769 | 0.001019 | 0.002299 | -0.000368 | -0.000685 |
| LFC2 | -0.738421 | 0.175254 | -0.508032 | 0.261357 | 0.232297 | 0.073713 | -0.130949 | -0.088457 | 0.032159 | 0.005121 | -0.024233 | 0.028131 | 0.008474 | 0.036443 | -0.009950 | -0.034634 | 0.039685 | 0.030584 | -0.010700 | -0.007812 | 0.014216 | -0.023334 | -0.012776 | 0.011840 | -0.016434 | -0.001305 | -0.001927 | -0.014804 | -0.001067 | 0.002255 | -0.004976 | 0.002452 | -0.005596 | 0.002908 | 0.010853 | 0.009159 | -0.003964 | -0.004134 | -0.001969 | 0.013122 | 0.014122 | 0.005036 | -0.005570 | -0.017329 | -0.004313 | 0.008975 | -0.003297 | -0.006800 | -0.011187 | 0.000539 | 0.000097 | 0.003221 | 0.001736 | 0.003922 | 0.001737 | -0.001450 | 0.007009 | -0.003549 | -0.000789 | 0.003602 | -0.000138 | 0.001207 | 0.002102 | -0.001301 | -0.006372 | -0.004996 | -0.005180 | -0.000304 | 0.003818 | 0.006413 | -0.007105 | 0.001778 | 0.003755 | 0.003506 | -0.006001 | -0.001858 |
| LFC3 | -0.661745 | 0.065135 | -0.582714 | 0.335290 | 0.226438 | 0.127728 | -0.071356 | -0.055000 | 0.043425 | 0.113834 | 0.005703 | 0.029829 | -0.012571 | 0.013113 | 0.020922 | -0.043147 | 0.042028 | -0.045871 | 0.009507 | -0.008492 | 0.034912 | -0.048021 | 0.000740 | -0.005042 | -0.012619 | -0.017961 | -0.025686 | -0.009237 | -0.004444 | -0.014505 | 0.012664 | 0.006495 | -0.003830 | 0.004587 | -0.007437 | 0.008953 | 0.009836 | -0.001923 | 0.013917 | -0.001152 | -0.008428 | -0.001015 | -0.001122 | -0.003542 | -0.006445 | -0.002110 | 0.008531 | 0.002491 | 0.003320 | -0.003216 | -0.006470 | -0.002461 | -0.008309 | -0.005907 | -0.001575 | 0.005017 | 0.002990 | 0.001298 | -0.001460 | 0.000036 | -0.004031 | -0.000308 | 0.000940 | -0.001866 | -0.004216 | -0.001791 | 0.006931 | 0.000340 | 0.008659 | -0.001006 | -0.000572 | 0.002537 | -0.002074 | 0.001466 | 0.004697 | 0.000431 |
| LFC4 | -0.814813 | 0.133678 | -0.405155 | 0.279269 | 0.188971 | 0.080599 | -0.128154 | -0.066430 | 0.030301 | 0.004720 | -0.012078 | 0.020819 | 0.016645 | 0.038480 | -0.011693 | -0.031622 | 0.047607 | 0.027878 | -0.006979 | -0.013815 | 0.015268 | -0.022298 | -0.014302 | 0.010761 | -0.012456 | 0.002265 | -0.000862 | -0.017180 | -0.001480 | 0.002109 | -0.007286 | -0.000894 | -0.004879 | 0.001730 | 0.010921 | 0.009038 | -0.006461 | -0.003884 | -0.003146 | 0.012646 | 0.014130 | 0.005868 | -0.005184 | -0.017778 | -0.004977 | 0.007817 | -0.003418 | -0.006273 | -0.010102 | 0.002721 | -0.000228 | 0.002403 | 0.001911 | 0.004065 | 0.002086 | -0.001786 | 0.006481 | -0.002783 | -0.002911 | 0.003046 | 0.000083 | 0.001565 | 0.000265 | -0.001579 | -0.006657 | -0.004594 | -0.005828 | 0.000006 | 0.002186 | 0.006688 | -0.007012 | 0.001761 | 0.004367 | 0.003535 | -0.005769 | -0.001933 |
| LFC5 | -0.733275 | 0.030659 | -0.493082 | 0.343380 | 0.209586 | 0.138300 | -0.080962 | -0.033359 | 0.042232 | 0.112166 | 0.013538 | 0.022803 | -0.010304 | 0.011361 | 0.020438 | -0.044204 | 0.044987 | -0.046012 | 0.010455 | -0.012384 | 0.032654 | -0.047472 | 0.001027 | -0.006839 | -0.011102 | -0.016106 | -0.025152 | -0.009691 | -0.006050 | -0.015770 | 0.011420 | 0.006363 | -0.004464 | 0.003289 | -0.008732 | 0.008939 | 0.008786 | -0.001699 | 0.014107 | -0.001256 | -0.007480 | -0.000995 | -0.002348 | -0.004077 | -0.007569 | -0.002754 | 0.008193 | 0.002578 | 0.004168 | -0.002521 | -0.006523 | -0.003108 | -0.008305 | -0.006444 | -0.001459 | 0.005873 | 0.002490 | 0.001449 | -0.002480 | -0.000384 | -0.003579 | -0.000402 | 0.000831 | -0.002046 | -0.005232 | -0.002600 | 0.007254 | 0.001357 | 0.008725 | -0.000987 | -0.001244 | 0.002319 | -0.001852 | 0.001659 | 0.005268 | 0.000011 |
| LFC6 | -0.477970 | 0.138759 | 0.194963 | 0.505433 | 0.484817 | 0.142571 | -0.062737 | 0.062303 | -0.003494 | 0.200986 | 0.154895 | -0.076422 | 0.009568 | 0.022573 | 0.020714 | -0.082174 | 0.105352 | -0.108622 | 0.084026 | -0.089877 | 0.112487 | -0.126229 | 0.021898 | -0.034353 | -0.003327 | -0.065341 | -0.071396 | -0.016285 | -0.020185 | -0.082979 | 0.034629 | -0.026122 | -0.018476 | -0.031355 | -0.013471 | 0.046942 | -0.007966 | -0.007594 | 0.044875 | -0.031114 | -0.033247 | 0.015777 | 0.010123 | 0.018902 | -0.018738 | -0.012042 | 0.036998 | 0.018779 | 0.018414 | 0.003169 | -0.018402 | -0.000855 | -0.039042 | -0.035150 | -0.013768 | 0.020451 | 0.003522 | 0.001587 | -0.013357 | 0.013623 | -0.022054 | 0.002248 | -0.007927 | -0.004562 | -0.012439 | 0.010841 | 0.053837 | -0.011328 | 0.021577 | 0.001333 | 0.008671 | -0.010068 | -0.004777 | 0.006799 | 0.029526 | 0.009621 |
| LFC7 | -0.706102 | 0.391162 | 0.309281 | 0.312441 | 0.168158 | 0.110624 | -0.135923 | 0.104107 | -0.029324 | 0.087339 | 0.119738 | -0.080571 | 0.007136 | 0.045403 | -0.009598 | -0.018203 | 0.058770 | -0.052272 | 0.033485 | -0.054554 | 0.071925 | -0.067919 | -0.000025 | -0.020763 | -0.014071 | -0.046962 | -0.038282 | -0.008315 | -0.014069 | -0.029854 | 0.004063 | -0.010002 | -0.027738 | -0.012948 | -0.009529 | 0.025341 | -0.010742 | -0.004253 | 0.024928 | -0.009446 | -0.023784 | -0.000827 | 0.001437 | -0.016029 | -0.052035 | -0.004408 | 0.052020 | 0.019825 | 0.027173 | 0.009469 | -0.023459 | -0.012957 | -0.038870 | -0.036668 | -0.011662 | 0.017152 | 0.003878 | -0.004719 | -0.012532 | 0.005971 | -0.012527 | 0.003589 | 0.001431 | -0.009669 | -0.028695 | 0.006570 | 0.044360 | 0.003767 | 0.008597 | 0.017430 | -0.007979 | -0.012010 | -0.000796 | 0.011182 | 0.032718 | 0.016578 |
| LFC8 | -0.510387 | 0.015631 | -0.093228 | 0.524446 | 0.339446 | 0.063537 | 0.001232 | 0.030597 | 0.029339 | 0.050172 | 0.136547 | -0.030555 | 0.022924 | 0.047985 | 0.042450 | -0.080638 | 0.086618 | -0.065880 | 0.067067 | -0.087865 | 0.075408 | -0.178322 | 0.033596 | -0.021995 | 0.046566 | -0.081576 | -0.045125 | -0.023459 | -0.002374 | -0.137888 | 0.050092 | -0.057523 | 0.045372 | -0.092621 | 0.046296 | 0.061919 | -0.003433 | 0.002523 | 0.024174 | -0.052695 | -0.012065 | 0.084204 | 0.059026 | 0.173715 | 0.182360 | -0.021892 | -0.099785 | -0.004840 | -0.056318 | 0.011483 | 0.040701 | 0.072801 | 0.026983 | 0.034254 | -0.020704 | -0.039917 | -0.012234 | -0.018861 | 0.031983 | 0.036500 | -0.024605 | -0.009402 | -0.058747 | 0.018899 | 0.156620 | 0.057258 | -0.057236 | -0.107824 | -0.029369 | -0.074685 | 0.093554 | 0.007950 | -0.013972 | -0.032969 | -0.058364 | -0.033107 |
| LFC9 | 0.178036 | 0.480580 | -0.508520 | 0.256789 | -0.055585 | -0.207206 | -0.112735 | -0.142244 | 0.019601 | 0.006877 | 0.063182 | -0.039567 | 0.068756 | 0.063944 | 0.213175 | -0.081775 | -0.048915 | 0.027469 | 0.071890 | -0.008437 | 0.026014 | -0.023340 | 0.018402 | -0.011057 | 0.025989 | 0.006001 | 0.000791 | 0.044084 | 0.021979 | -0.032773 | 0.045695 | -0.003445 | 0.030028 | -0.057155 | 0.027773 | 0.028341 | -0.025831 | -0.006164 | -0.053622 | -0.018661 | 0.019976 | 0.052654 | 0.005665 | 0.087245 | 0.127583 | 0.045933 | -0.098063 | -0.104783 | -0.067106 | -0.083797 | 0.096174 | -0.031122 | 0.114042 | 0.161383 | -0.030016 | -0.005242 | -0.002946 | 0.113655 | -0.082732 | 0.052849 | 0.131972 | -0.017490 | -0.019632 | 0.059774 | -0.121806 | -0.039374 | 0.160754 | 0.044702 | 0.065888 | 0.074549 | -0.104169 | 0.068347 | 0.033083 | -0.024058 | 0.035425 | -0.003801 |
| LFC10 | 0.832402 | -0.047740 | -0.300965 | -0.295834 | 0.086881 | -0.109494 | 0.119490 | -0.176010 | -0.010358 | -0.023623 | -0.088897 | 0.003188 | -0.001774 | -0.042707 | 0.002962 | -0.000428 | -0.072529 | 0.009421 | -0.033812 | 0.069947 | -0.055868 | 0.097378 | -0.012699 | 0.033306 | -0.018898 | 0.044864 | 0.001709 | 0.015099 | -0.001402 | 0.050061 | -0.004394 | 0.030261 | -0.001093 | 0.050944 | -0.030993 | -0.013844 | 0.024855 | 0.011838 | -0.008523 | 0.015249 | -0.002408 | -0.026113 | -0.012945 | -0.039657 | -0.035709 | -0.004508 | 0.020235 | 0.003987 | 0.019233 | -0.016816 | 0.003572 | -0.025345 | -0.003853 | 0.005253 | 0.006069 | 0.006245 | -0.004594 | 0.011869 | -0.003856 | -0.015775 | -0.000623 | 0.002287 | 0.000979 | -0.007546 | -0.022293 | -0.012205 | -0.001054 | 0.014870 | 0.014048 | -0.000660 | -0.001072 | 0.002714 | -0.006486 | -0.000916 | 0.008388 | -0.002669 |
| OCC1 | -0.779628 | -0.480885 | 0.238294 | -0.036022 | 0.055140 | 0.202754 | 0.060079 | -0.128396 | -0.120691 | 0.002456 | 0.027472 | -0.051771 | -0.053118 | -0.005897 | 0.012992 | 0.019711 | 0.055551 | 0.000802 | -0.065069 | 0.010040 | 0.015336 | 0.041962 | 0.035312 | 0.007171 | -0.000395 | -0.019830 | 0.017539 | -0.002296 | 0.008422 | -0.003834 | -0.004918 | 0.010831 | 0.030596 | -0.001734 | 0.018546 | -0.006922 | -0.009103 | 0.013652 | -0.004454 | 0.004689 | -0.009722 | -0.003309 | -0.000384 | 0.004523 | -0.001469 | 0.016737 | 0.011770 | -0.003667 | -0.000737 | -0.005443 | -0.006372 | 0.000163 | -0.002607 | 0.008405 | -0.009394 | 0.000203 | 0.015392 | -0.002181 | 0.000207 | -0.000004 | 0.006521 | 0.010507 | -0.001550 | 0.004964 | 0.007809 | 0.006936 | 0.002404 | -0.001052 | -0.004947 | -0.001559 | -0.003918 | 0.003289 | -0.000432 | -0.000993 | 0.004214 | -0.002125 |
| OCC2 | -0.877336 | -0.428811 | 0.167395 | 0.016751 | -0.010155 | 0.018619 | 0.054829 | -0.075829 | -0.005719 | -0.039698 | -0.006055 | -0.003615 | -0.008944 | 0.007894 | -0.010283 | -0.015343 | 0.011388 | 0.011091 | -0.017266 | -0.012144 | -0.008827 | -0.001645 | -0.007872 | 0.004469 | -0.011478 | 0.002275 | 0.001984 | 0.001102 | 0.018988 | -0.008783 | 0.000742 | 0.002570 | -0.008241 | 0.008825 | -0.002386 | -0.007053 | 0.007943 | 0.003707 | 0.001059 | -0.002620 | 0.007075 | -0.001821 | 0.004662 | -0.005133 | 0.007911 | -0.008529 | 0.000271 | -0.002412 | 0.004324 | -0.003171 | -0.000575 | -0.000158 | 0.002718 | 0.005903 | 0.000272 | -0.005686 | 0.001072 | 0.003938 | -0.004277 | -0.006002 | -0.003955 | 0.002718 | -0.002536 | -0.000063 | 0.000676 | -0.000858 | -0.004961 | 0.004882 | 0.002517 | -0.005252 | 0.001745 | 0.007360 | -0.000307 | 0.004573 | -0.002534 | 0.001109 |
| OCC3 | -0.629532 | -0.362769 | -0.307321 | 0.351960 | 0.183367 | 0.066240 | 0.112909 | 0.078305 | -0.039977 | 0.088623 | 0.036634 | -0.109339 | 0.001048 | -0.039071 | -0.000760 | 0.039369 | 0.078686 | 0.024829 | -0.065598 | 0.025631 | -0.034787 | 0.082075 | 0.038365 | 0.034289 | 0.022762 | -0.057715 | -0.015166 | 0.077136 | -0.003654 | -0.003338 | -0.016301 | 0.071299 | 0.059943 | -0.013587 | -0.011135 | 0.012988 | -0.088911 | -0.087836 | 0.037233 | 0.024987 | -0.048703 | -0.061866 | 0.014974 | 0.017522 | -0.013831 | -0.045105 | -0.055304 | 0.058550 | -0.000191 | 0.025806 | 0.055836 | 0.039597 | 0.090220 | -0.067399 | 0.018796 | -0.042385 | -0.088514 | -0.033523 | 0.007871 | -0.034806 | 0.026117 | -0.067633 | -0.022560 | 0.029611 | 0.031639 | -0.044864 | 0.018902 | 0.015796 | 0.005117 | 0.062004 | -0.005178 | -0.037930 | 0.079406 | 0.047331 | -0.019098 | 0.003138 |
| OCC4 | -0.745706 | -0.444339 | 0.329704 | 0.150046 | 0.065345 | -0.120159 | 0.109983 | -0.062445 | -0.013242 | -0.133362 | 0.020345 | 0.082840 | 0.022201 | 0.018728 | -0.018406 | -0.044690 | -0.033452 | -0.047409 | 0.007971 | 0.003471 | -0.066971 | -0.039037 | -0.022014 | 0.031109 | 0.013734 | 0.025042 | 0.013201 | -0.023711 | -0.030053 | -0.035965 | 0.000376 | -0.062929 | -0.035757 | 0.059404 | -0.055115 | -0.037755 | 0.040168 | 0.056595 | 0.058204 | -0.011396 | -0.015505 | 0.011392 | 0.028021 | -0.006418 | -0.009236 | 0.005576 | 0.002938 | -0.048209 | -0.021434 | -0.012647 | -0.021352 | 0.017933 | 0.007179 | -0.014195 | -0.020655 | 0.008136 | 0.002876 | -0.009578 | -0.006813 | -0.012995 | 0.023805 | -0.002257 | -0.002859 | 0.016191 | 0.006591 | 0.005506 | 0.002754 | 0.008701 | -0.012543 | -0.009637 | -0.018450 | -0.009096 | 0.016793 | 0.000715 | 0.008471 | -0.002774 |
| OCC5 | -0.270144 | -0.231355 | -0.393370 | 0.275432 | 0.580392 | -0.157786 | 0.139095 | 0.311132 | 0.087692 | 0.171599 | 0.091481 | -0.020625 | -0.074992 | -0.025223 | 0.021532 | 0.020373 | 0.007888 | 0.072130 | -0.017303 | 0.019149 | -0.064238 | -0.058274 | -0.026342 | -0.064838 | 0.046288 | 0.080339 | -0.054111 | 0.048034 | -0.009600 | 0.005557 | -0.010029 | -0.020360 | -0.085090 | 0.017648 | 0.000052 | 0.036462 | 0.030569 | 0.002928 | 0.048031 | -0.066322 | 0.031683 | -0.025823 | 0.011183 | 0.010317 | -0.001712 | -0.059032 | -0.026823 | 0.046668 | 0.031050 | -0.021659 | -0.002501 | -0.017650 | -0.006472 | -0.007492 | 0.052808 | -0.000653 | 0.012820 | 0.037079 | 0.016033 | 0.029858 | -0.070304 | 0.026603 | -0.003797 | -0.025831 | -0.029965 | -0.054111 | 0.001836 | 0.010905 | 0.069134 | -0.026709 | 0.032863 | 0.019443 | -0.046413 | -0.025231 | -0.025577 | -0.021362 |
| OCC6 | 0.471152 | -0.213309 | -0.150573 | -0.485184 | 0.054335 | -0.089099 | 0.041133 | -0.247570 | -0.047407 | -0.040345 | -0.106522 | 0.077838 | -0.049161 | 0.025982 | -0.011035 | -0.012925 | 0.086735 | -0.045397 | 0.120762 | -0.055902 | -0.014967 | -0.107669 | 0.045708 | -0.055030 | -0.048510 | -0.074814 | 0.050705 | -0.084623 | -0.107456 | 0.090256 | -0.183269 | 0.074042 | 0.075752 | 0.021181 | -0.123062 | 0.041584 | -0.007020 | -0.061936 | -0.063850 | -0.118121 | 0.144481 | -0.092625 | -0.149458 | 0.109950 | 0.030405 | -0.129076 | -0.031456 | 0.023567 | 0.124055 | 0.037247 | -0.008552 | 0.054571 | 0.012055 | 0.021345 | -0.084656 | -0.003445 | 0.097778 | -0.157140 | -0.013126 | -0.026536 | 0.088787 | -0.043804 | -0.011923 | 0.034792 | -0.015143 | -0.011382 | 0.025760 | 0.035966 | 0.056625 | -0.092476 | -0.009132 | -0.025910 | 0.031647 | -0.005196 | 0.041337 | 0.019332 |
| OCC7 | 0.338682 | 0.130981 | -0.217486 | 0.115814 | 0.131728 | -0.284316 | 0.397381 | 0.119504 | -0.119320 | 0.174057 | -0.038237 | -0.073005 | -0.111496 | -0.116478 | 0.087327 | 0.128541 | -0.042189 | 0.117213 | -0.100070 | 0.008238 | 0.128682 | -0.171892 | 0.105603 | -0.034092 | -0.007847 | 0.130752 | -0.083800 | 0.108329 | 0.022576 | 0.097509 | -0.039626 | -0.063049 | -0.160105 | -0.131249 | -0.072534 | 0.046576 | 0.199954 | -0.028883 | -0.193361 | 0.120537 | -0.042199 | 0.045793 | -0.036070 | -0.062154 | 0.079140 | -0.045571 | 0.042233 | -0.022157 | -0.065038 | 0.021822 | -0.002556 | 0.039627 | 0.045647 | -0.066261 | 0.058168 | -0.018921 | -0.044203 | -0.079418 | -0.083552 | -0.100143 | 0.064167 | -0.005859 | 0.016540 | 0.014777 | 0.018461 | 0.084602 | -0.038836 | -0.037473 | -0.013585 | 0.022390 | -0.070472 | -0.012593 | 0.017240 | -0.028318 | 0.013674 | 0.056085 |
| OCC8 | 0.925336 | 0.075649 | -0.163459 | -0.000387 | 0.178948 | -0.075852 | 0.012617 | -0.069112 | -0.108509 | 0.019071 | -0.050314 | 0.024829 | 0.007784 | 0.018793 | -0.008521 | -0.018689 | -0.105555 | -0.093692 | 0.042232 | -0.006735 | -0.028860 | -0.043063 | 0.032633 | -0.016638 | -0.058126 | -0.042982 | -0.026588 | -0.013291 | -0.041850 | -0.020087 | -0.005744 | 0.025456 | 0.028159 | -0.021858 | -0.030014 | 0.006231 | 0.005573 | -0.010625 | -0.010087 | 0.019829 | -0.000024 | 0.004837 | -0.027193 | 0.015680 | -0.013887 | 0.031586 | 0.001190 | -0.001112 | -0.011681 | -0.009436 | 0.016545 | -0.006184 | -0.008290 | -0.001467 | 0.009509 | 0.010698 | -0.031123 | 0.012147 | 0.006922 | -0.009239 | -0.004133 | 0.000284 | 0.010346 | -0.004477 | -0.003057 | 0.025901 | 0.005999 | -0.012593 | -0.004562 | 0.005184 | 0.002828 | 0.005508 | -0.004244 | 0.006726 | 0.000969 | 0.005143 |
| OCC9 | 0.510494 | 0.606883 | 0.228532 | -0.082238 | -0.243560 | -0.023479 | -0.321633 | -0.172415 | -0.141240 | 0.074765 | -0.014575 | -0.082598 | -0.123029 | 0.092286 | -0.022664 | -0.070163 | 0.059706 | -0.002787 | 0.100440 | 0.042097 | -0.017610 | -0.017197 | -0.108168 | 0.050025 | 0.066052 | 0.087898 | -0.025558 | -0.029825 | 0.024211 | 0.004877 | -0.003269 | 0.009477 | -0.000251 | -0.032509 | 0.018142 | -0.000621 | -0.000260 | -0.039796 | -0.026844 | 0.014954 | -0.025924 | 0.005500 | -0.005180 | 0.001439 | 0.005281 | 0.008831 | -0.000081 | -0.001840 | -0.005861 | -0.009178 | -0.005213 | 0.001679 | 0.016609 | -0.003051 | -0.000710 | 0.002067 | 0.005649 | -0.003788 | 0.023755 | -0.014803 | 0.009782 | -0.017611 | -0.006953 | -0.033670 | -0.004312 | -0.015932 | 0.001314 | -0.006832 | -0.008007 | -0.005372 | 0.001009 | -0.011392 | -0.019318 | 0.013252 | 0.004487 | -0.020677 |
| OCC10 | 0.495835 | 0.753671 | -0.122191 | 0.151122 | 0.061510 | -0.237326 | -0.145187 | 0.089194 | 0.112943 | 0.021324 | -0.055329 | 0.029228 | 0.063107 | -0.070504 | 0.016176 | 0.061664 | -0.034912 | 0.050622 | -0.010869 | -0.015477 | 0.015453 | -0.000449 | 0.033400 | 0.009858 | -0.020289 | -0.005095 | 0.033366 | 0.004912 | -0.002190 | 0.002512 | -0.025759 | -0.014102 | 0.017966 | -0.000601 | 0.010167 | 0.025924 | -0.054198 | 0.000133 | -0.001571 | 0.022743 | 0.012291 | -0.007144 | -0.000520 | -0.041142 | 0.004292 | 0.006888 | -0.030463 | -0.002036 | 0.016693 | 0.031722 | -0.003690 | -0.007724 | -0.019234 | 0.021045 | 0.012566 | 0.015181 | -0.003664 | -0.008639 | -0.018951 | 0.033604 | -0.015590 | 0.000195 | -0.011523 | 0.003283 | -0.011191 | -0.007244 | -0.005293 | -0.003611 | -0.016768 | 0.002614 | 0.007339 | 0.005993 | 0.009867 | -0.001723 | -0.009355 | -0.016685 |
| OCC11 | 0.720812 | 0.567890 | -0.161824 | -0.062518 | 0.141074 | -0.001984 | -0.119258 | -0.037683 | 0.196426 | -0.041733 | 0.032459 | 0.022826 | 0.130525 | 0.018349 | -0.012215 | 0.026923 | 0.025841 | -0.019370 | 0.022928 | -0.005276 | 0.098523 | 0.068886 | -0.013725 | 0.000799 | -0.006971 | -0.059207 | 0.017805 | 0.000776 | 0.034702 | 0.027233 | 0.030305 | 0.014654 | 0.006620 | -0.007376 | 0.002573 | 0.004492 | 0.023264 | -0.005128 | -0.015593 | -0.011475 | -0.000510 | 0.008769 | 0.017082 | -0.013529 | 0.016302 | -0.023422 | 0.027607 | 0.001404 | 0.008276 | -0.003362 | 0.002387 | -0.004812 | 0.014009 | -0.010066 | -0.018548 | -0.008386 | 0.006136 | 0.012309 | 0.008767 | 0.006693 | -0.001170 | 0.011175 | 0.016155 | -0.000513 | 0.007579 | -0.003056 | 0.002641 | 0.008997 | -0.000249 | -0.000575 | -0.006258 | -0.000535 | -0.002102 | -0.005352 | -0.005650 | 0.005009 |
| OCC12 | 0.698787 | 0.657026 | -0.068404 | 0.011414 | 0.038945 | -0.113911 | -0.070990 | -0.023549 | 0.067328 | 0.031874 | -0.033788 | 0.008004 | 0.018679 | -0.024616 | 0.001700 | 0.004242 | -0.020342 | 0.050172 | -0.008891 | 0.010087 | -0.035673 | -0.031983 | -0.006923 | -0.042362 | 0.007136 | 0.028404 | -0.013487 | 0.018423 | -0.001527 | 0.050114 | 0.022930 | 0.008693 | -0.022747 | 0.029947 | 0.076537 | -0.038401 | -0.035649 | -0.003058 | -0.009818 | -0.006062 | 0.009972 | 0.008827 | -0.019692 | 0.065963 | -0.029505 | 0.038874 | 0.010653 | 0.026649 | -0.025578 | 0.015553 | 0.009235 | -0.011448 | -0.032120 | -0.000955 | -0.009825 | -0.005775 | 0.009085 | -0.004168 | -0.005421 | 0.008388 | 0.013283 | 0.009869 | 0.000555 | 0.013039 | 0.009528 | 0.017384 | -0.008013 | 0.003770 | 0.007847 | -0.000126 | -0.007919 | -0.008317 | 0.002251 | -0.007196 | 0.013760 | 0.029053 |
| OCC13 | 0.788821 | 0.495232 | -0.209795 | -0.057653 | 0.118598 | -0.105541 | -0.079366 | -0.032819 | 0.058187 | -0.036065 | -0.025728 | 0.030866 | 0.053367 | -0.009134 | -0.006084 | 0.021041 | -0.033068 | -0.004300 | 0.013952 | -0.010507 | 0.028510 | 0.009501 | -0.012546 | -0.008886 | -0.016315 | -0.016910 | 0.007891 | -0.011932 | -0.004020 | 0.001756 | 0.044069 | -0.005795 | -0.013142 | -0.015075 | 0.017200 | -0.003449 | -0.015306 | 0.000747 | 0.009277 | 0.006686 | 0.010245 | 0.023724 | -0.000577 | -0.006647 | -0.005539 | 0.001743 | -0.000442 | -0.000847 | 0.004199 | 0.021902 | 0.003613 | -0.001795 | -0.025283 | 0.027762 | -0.008705 | -0.007021 | 0.008772 | 0.000447 | -0.003985 | 0.004287 | 0.008708 | -0.041244 | 0.008710 | 0.006420 | -0.011779 | 0.008738 | -0.015496 | -0.028762 | -0.018478 | 0.038867 | 0.024201 | -0.011303 | 0.004469 | -0.014973 | 0.018351 | 0.025251 |
| EIC1 | 0.466804 | 0.617246 | 0.239932 | -0.076804 | -0.250568 | -0.013479 | -0.333010 | -0.173223 | -0.157602 | 0.072817 | -0.013147 | -0.089233 | -0.130243 | 0.093965 | -0.022952 | -0.075146 | 0.063232 | 0.001095 | 0.104706 | 0.041980 | -0.014766 | -0.017481 | -0.113399 | 0.050538 | 0.070335 | 0.095676 | -0.028545 | -0.032825 | 0.024982 | 0.006465 | -0.004434 | 0.007169 | -0.001891 | -0.031105 | 0.018721 | -0.004502 | -0.000876 | -0.044532 | -0.025852 | 0.016867 | -0.026511 | 0.004766 | -0.004304 | 0.001948 | 0.003927 | 0.008124 | -0.002998 | -0.002797 | -0.006214 | -0.010186 | -0.005082 | 0.003002 | 0.016433 | -0.002506 | 0.000257 | 0.001560 | 0.006201 | -0.006089 | 0.024452 | -0.015192 | 0.009900 | -0.020574 | -0.007823 | -0.035726 | -0.006260 | -0.015035 | 0.002025 | -0.007549 | -0.007432 | -0.005917 | 0.001913 | -0.011913 | -0.020073 | 0.014493 | 0.004355 | -0.022436 |
| EIC2 | 0.224802 | 0.520377 | 0.111966 | -0.017699 | -0.138037 | 0.038968 | -0.022621 | -0.143149 | -0.145249 | -0.174942 | -0.012053 | 0.004415 | -0.005018 | -0.115278 | -0.033645 | -0.095996 | 0.008825 | 0.137794 | -0.245458 | 0.029710 | -0.150817 | -0.218140 | 0.009938 | -0.055309 | -0.028169 | -0.013471 | 0.101210 | 0.014094 | 0.111391 | 0.034964 | -0.147005 | 0.015966 | -0.004593 | 0.144301 | 0.119777 | -0.123387 | -0.205709 | 0.003674 | -0.081372 | 0.132162 | -0.009544 | -0.070496 | 0.011614 | 0.035816 | 0.177130 | 0.064927 | -0.042546 | -0.039521 | -0.022179 | 0.100372 | 0.036028 | 0.024609 | -0.071937 | -0.155184 | -0.101202 | 0.026379 | -0.172841 | -0.015273 | -0.111464 | 0.093461 | -0.036712 | 0.059768 | 0.021429 | -0.101808 | -0.023363 | 0.023362 | -0.038645 | 0.041906 | 0.123129 | -0.062009 | -0.004067 | -0.042502 | -0.006720 | -0.007875 | 0.095326 | -0.047871 |
| EIC3 | 0.275613 | 0.649811 | -0.004175 | 0.194218 | -0.168770 | -0.470358 | -0.129634 | -0.032610 | 0.068141 | 0.047582 | -0.170844 | 0.018446 | -0.002120 | -0.151830 | 0.046978 | 0.092602 | -0.039474 | 0.028193 | -0.004737 | -0.086179 | 0.006455 | -0.019436 | 0.044398 | 0.042109 | -0.028235 | 0.028332 | 0.064382 | -0.018590 | -0.042987 | -0.047148 | -0.016475 | -0.041762 | 0.049208 | -0.036621 | -0.006794 | 0.056361 | -0.099108 | 0.028285 | 0.034458 | 0.029565 | 0.048775 | 0.015376 | -0.037794 | -0.072092 | -0.012752 | 0.034798 | -0.052022 | -0.003606 | 0.026050 | 0.076548 | -0.020860 | -0.024714 | -0.065396 | 0.084809 | 0.056845 | 0.031561 | 0.017538 | -0.014024 | -0.058630 | 0.027980 | -0.030037 | -0.043049 | -0.048248 | 0.012915 | -0.036432 | -0.055923 | -0.050666 | -0.034132 | -0.052974 | 0.042530 | 0.039049 | 0.023364 | 0.035121 | 0.000567 | -0.021645 | -0.028127 |
| EIC4 | 0.218312 | 0.698452 | -0.186975 | -0.015806 | 0.250857 | 0.026483 | -0.224973 | 0.013140 | 0.391606 | -0.082354 | 0.060192 | 0.011193 | 0.232420 | -0.008007 | -0.023628 | 0.036757 | 0.001943 | -0.003073 | 0.047000 | 0.037063 | 0.167347 | 0.151615 | -0.035165 | 0.018885 | -0.022803 | -0.101835 | 0.020206 | 0.015639 | 0.059958 | 0.038641 | 0.037441 | 0.015785 | 0.016099 | -0.007316 | 0.027057 | 0.007658 | 0.032277 | -0.019811 | -0.035202 | -0.021041 | -0.000064 | 0.009510 | 0.032554 | -0.015915 | 0.026026 | -0.050709 | 0.036514 | 0.005652 | 0.009778 | 0.003886 | 0.008112 | 0.000884 | 0.037367 | -0.015540 | -0.036395 | -0.016255 | 0.010566 | 0.005261 | 0.020300 | 0.008709 | -0.003685 | 0.023903 | 0.026331 | -0.000545 | 0.017881 | -0.017247 | 0.005027 | 0.017509 | -0.015068 | -0.003525 | -0.007368 | 0.004046 | 0.002556 | 0.001410 | -0.013055 | 0.001532 |
| EIC5 | -0.018320 | 0.349467 | -0.460912 | 0.093178 | 0.248055 | -0.249672 | 0.089508 | 0.152741 | 0.247201 | 0.174328 | -0.025787 | -0.005907 | -0.067946 | 0.045423 | -0.015027 | -0.036320 | -0.038966 | 0.117345 | 0.009706 | -0.066232 | -0.179393 | -0.103613 | -0.088562 | -0.097711 | -0.035154 | 0.117299 | -0.078562 | 0.112334 | 0.002823 | 0.136468 | 0.106994 | 0.039998 | -0.127318 | 0.077777 | 0.218481 | -0.056712 | -0.077766 | -0.056250 | 0.019162 | -0.107256 | 0.059630 | 0.000375 | -0.038310 | 0.218860 | -0.153884 | 0.038646 | 0.036469 | 0.104296 | -0.088800 | 0.032989 | 0.056600 | -0.067369 | -0.043695 | 0.037247 | 0.014262 | -0.011531 | 0.027189 | 0.013339 | 0.009068 | -0.013224 | -0.022411 | 0.001103 | 0.001662 | 0.066209 | 0.034820 | 0.015613 | -0.021141 | 0.029281 | -0.011486 | -0.015880 | -0.034937 | 0.026386 | -0.020901 | -0.003891 | 0.002701 | 0.047812 |
| EIC6 | -0.497018 | 0.267178 | -0.088176 | 0.284600 | 0.132691 | -0.111272 | 0.236047 | 0.061587 | 0.075130 | 0.030384 | -0.008129 | -0.092801 | -0.063956 | -0.148604 | 0.027800 | -0.038073 | 0.057227 | 0.073851 | -0.108200 | -0.089964 | -0.093469 | -0.117972 | -0.030011 | 0.011547 | -0.016450 | 0.047792 | -0.006758 | 0.018006 | 0.018462 | -0.008794 | -0.096084 | -0.063107 | -0.098914 | 0.009757 | 0.117485 | 0.079710 | -0.072200 | 0.077361 | 0.053028 | 0.070538 | -0.099965 | -0.186829 | -0.015217 | -0.149170 | 0.016915 | -0.067360 | -0.229752 | 0.055626 | 0.209635 | -0.069800 | 0.026374 | -0.000906 | 0.019763 | 0.065945 | 0.000253 | 0.006384 | 0.070992 | 0.127429 | 0.252803 | 0.035626 | 0.101823 | -0.057855 | 0.066801 | -0.006395 | 0.017534 | 0.118681 | 0.011249 | -0.082279 | 0.035026 | -0.006401 | -0.026714 | -0.031873 | -0.007760 | -0.042322 | 0.013771 | 0.119021 |
| EIC7 | -0.782611 | -0.094142 | -0.165812 | 0.066742 | 0.206563 | -0.098866 | -0.084336 | 0.088075 | 0.213522 | -0.203119 | 0.034756 | 0.027867 | -0.014794 | 0.021248 | -0.038790 | -0.075451 | 0.062833 | 0.009588 | 0.034629 | -0.006611 | -0.139181 | -0.010366 | -0.081186 | -0.006592 | 0.024033 | 0.084810 | -0.059526 | 0.019412 | -0.015987 | -0.019627 | 0.033708 | -0.020395 | -0.078208 | 0.052738 | 0.021091 | -0.063239 | -0.008135 | 0.038426 | 0.051975 | -0.042088 | 0.047327 | 0.027956 | 0.033269 | 0.001451 | 0.008661 | -0.000806 | -0.018162 | -0.014822 | -0.008120 | -0.036016 | -0.117814 | 0.017063 | 0.001544 | -0.067281 | -0.015205 | -0.042284 | 0.042345 | -0.032841 | -0.070049 | -0.102718 | 0.089079 | -0.003891 | -0.059438 | -0.015762 | -0.030230 | -0.035789 | 0.023516 | -0.058836 | 0.056544 | 0.101821 | 0.102968 | -0.016495 | 0.075665 | -0.054639 | -0.033961 | 0.040999 |
| EIC8 | 0.590364 | -0.092720 | 0.019902 | 0.407161 | 0.337802 | -0.286276 | 0.045313 | 0.010221 | -0.150506 | -0.104701 | 0.020980 | 0.171854 | 0.121389 | 0.016623 | -0.034615 | -0.013428 | -0.198910 | -0.129285 | 0.013397 | 0.033016 | -0.090527 | -0.070887 | 0.024506 | 0.050694 | -0.023086 | -0.007619 | -0.007631 | -0.050621 | -0.098138 | -0.076639 | 0.008452 | -0.128528 | -0.039463 | 0.070257 | -0.117394 | -0.049557 | 0.049844 | 0.037923 | 0.081423 | 0.008937 | -0.040612 | 0.041900 | 0.034326 | 0.014796 | -0.055719 | 0.037612 | -0.002076 | -0.075887 | -0.044486 | 0.020806 | 0.036574 | 0.022644 | -0.012536 | 0.025444 | -0.045799 | 0.028038 | -0.024153 | -0.010181 | 0.018405 | 0.018784 | 0.019492 | -0.039073 | 0.041779 | 0.029165 | 0.000290 | 0.048250 | -0.015655 | 0.001110 | -0.038743 | -0.035100 | -0.055373 | -0.035035 | 0.021609 | 0.016334 | 0.053777 | -0.007103 |
| EIC9 | -0.739128 | -0.607696 | 0.184702 | 0.023250 | 0.055836 | -0.059948 | 0.069388 | -0.023777 | 0.050963 | -0.042082 | -0.012387 | 0.013786 | -0.038842 | 0.047708 | -0.012361 | -0.033578 | 0.011244 | 0.001685 | -0.000250 | -0.020700 | -0.042101 | -0.027902 | -0.020566 | -0.017265 | 0.024428 | 0.026271 | 0.021609 | 0.006832 | 0.008092 | -0.006245 | 0.000052 | -0.016044 | -0.030394 | 0.022498 | -0.029478 | 0.003383 | 0.023247 | 0.019569 | 0.026935 | -0.007754 | -0.000782 | -0.000779 | -0.002641 | -0.010298 | 0.014167 | -0.022572 | 0.001438 | -0.006452 | 0.007523 | -0.013672 | -0.000921 | -0.001332 | 0.004132 | -0.005480 | 0.014159 | 0.011854 | 0.013326 | 0.006066 | -0.001754 | 0.009041 | -0.011995 | 0.001974 | -0.005491 | -0.011782 | -0.003452 | -0.018768 | -0.003065 | 0.023041 | 0.014458 | -0.014200 | 0.007537 | 0.015777 | -0.027800 | 0.004846 | -0.007505 | -0.021259 |
| EIC10 | -0.324705 | -0.585332 | -0.401450 | 0.030695 | 0.207769 | -0.297886 | -0.022623 | 0.039073 | 0.116613 | -0.003716 | -0.149957 | 0.082520 | -0.076222 | -0.033963 | 0.012020 | 0.036648 | 0.023961 | 0.022387 | 0.019704 | -0.046397 | -0.127344 | -0.020786 | -0.001136 | 0.037194 | 0.005279 | -0.013966 | -0.047558 | -0.005761 | 0.007497 | -0.047983 | -0.011274 | 0.048965 | -0.001805 | -0.020634 | -0.024910 | -0.026444 | -0.013925 | -0.055534 | -0.042889 | 0.025492 | 0.033407 | 0.003959 | 0.114172 | -0.095403 | 0.035803 | -0.016543 | 0.001651 | 0.070782 | 0.039604 | -0.024074 | 0.017533 | -0.001981 | -0.027256 | 0.034291 | 0.132169 | -0.049656 | -0.057655 | -0.136766 | -0.065921 | 0.031495 | -0.084386 | 0.056046 | -0.068156 | 0.075443 | 0.026406 | 0.132236 | 0.138012 | 0.022227 | -0.000399 | 0.025430 | -0.049585 | 0.014569 | -0.086973 | 0.002923 | -0.010523 | 0.042093 |
| EIC11 | 0.619133 | -0.407218 | -0.037091 | -0.017783 | 0.000853 | -0.323624 | 0.075076 | -0.139173 | -0.135083 | 0.063634 | -0.116711 | 0.128612 | -0.010998 | 0.018711 | 0.008363 | -0.065907 | -0.083196 | -0.204903 | 0.089301 | -0.104149 | -0.027457 | -0.169467 | 0.041589 | -0.029904 | -0.156407 | -0.055251 | 0.004420 | -0.097550 | -0.049686 | 0.013855 | -0.141247 | 0.090854 | 0.066222 | -0.047507 | -0.051514 | 0.003933 | 0.033195 | -0.012668 | -0.079988 | -0.055690 | 0.094689 | -0.040334 | -0.134537 | 0.049699 | 0.001463 | -0.019832 | 0.011578 | 0.006609 | 0.046439 | -0.013869 | 0.002804 | 0.007623 | 0.007239 | -0.013633 | -0.012011 | 0.003635 | -0.005773 | -0.001214 | -0.002285 | -0.035589 | 0.009784 | 0.022712 | -0.008499 | -0.015012 | -0.006789 | -0.038676 | -0.006323 | -0.011162 | 0.014330 | -0.016115 | -0.011264 | 0.024331 | 0.026081 | 0.011222 | -0.026387 | 0.041619 |
| EIC12 | -0.271404 | -0.729949 | 0.085901 | 0.076357 | -0.072819 | -0.247279 | -0.013426 | -0.053354 | -0.079718 | 0.044025 | -0.125165 | 0.134793 | -0.047140 | -0.055240 | 0.057754 | 0.018213 | -0.058047 | -0.126200 | 0.067989 | -0.048098 | 0.002898 | -0.117287 | 0.086319 | 0.000490 | -0.060226 | -0.045151 | -0.028975 | -0.086196 | 0.003705 | 0.055483 | -0.120516 | 0.084549 | 0.021970 | -0.094889 | 0.034300 | 0.019214 | 0.037309 | 0.102817 | -0.099844 | -0.035348 | -0.014923 | -0.043052 | -0.025279 | -0.006039 | -0.005059 | 0.105530 | 0.010466 | -0.009688 | -0.045441 | -0.096071 | -0.061417 | -0.015769 | 0.033209 | -0.070568 | 0.065956 | -0.013103 | -0.051623 | 0.183030 | 0.025370 | -0.063626 | -0.027304 | 0.093807 | 0.001364 | 0.031000 | 0.035280 | -0.018708 | -0.048274 | -0.002853 | -0.021490 | 0.046646 | 0.021689 | 0.040755 | -0.035914 | 0.000385 | -0.035065 | -0.027788 |
| EIC13 | -0.102353 | -0.396116 | 0.344588 | -0.037894 | 0.455564 | 0.281679 | 0.277736 | -0.125950 | -0.136407 | -0.035235 | 0.034594 | -0.147514 | -0.034778 | 0.100733 | -0.022622 | -0.028644 | 0.032696 | -0.027369 | -0.006922 | 0.036760 | -0.025050 | 0.110424 | 0.171429 | -0.082785 | 0.042267 | -0.046506 | -0.063333 | 0.148268 | -0.088955 | -0.034768 | -0.021735 | 0.072150 | 0.154108 | -0.028876 | -0.015012 | 0.043886 | -0.022421 | -0.071448 | 0.145616 | 0.094822 | -0.135460 | -0.031251 | -0.105299 | 0.051055 | -0.025660 | 0.050861 | -0.027501 | 0.033470 | -0.078450 | 0.015432 | -0.009424 | -0.012961 | 0.024217 | -0.072794 | 0.012723 | 0.043187 | -0.053096 | -0.032880 | -0.007339 | -0.030949 | 0.037998 | -0.041487 | 0.025335 | 0.009821 | -0.015374 | -0.016510 | 0.031602 | -0.053693 | 0.008210 | 0.069429 | 0.020752 | -0.016127 | -0.076061 | -0.005181 | -0.018336 | -0.006386 |
| EIC14 | -0.297416 | -0.045035 | 0.261946 | -0.112895 | 0.199038 | 0.480577 | 0.147005 | -0.249261 | -0.420401 | 0.113559 | 0.240837 | -0.141346 | -0.169509 | -0.131517 | 0.079353 | 0.142856 | 0.095169 | -0.053326 | -0.171718 | 0.122316 | 0.080521 | 0.033972 | 0.050647 | -0.007349 | 0.025565 | -0.015767 | 0.055384 | -0.023339 | -0.042464 | 0.003704 | 0.030026 | -0.045699 | 0.022520 | -0.003602 | 0.048182 | -0.008164 | -0.043181 | 0.077682 | -0.063612 | -0.014781 | 0.034181 | 0.031865 | -0.001927 | 0.040298 | -0.033915 | 0.046870 | 0.023315 | -0.001170 | 0.034343 | -0.022894 | -0.017069 | 0.000510 | -0.046441 | 0.033093 | -0.036310 | 0.016885 | 0.045905 | -0.027134 | 0.018395 | 0.020309 | 0.016392 | 0.056486 | -0.005388 | 0.006592 | -0.002946 | 0.011376 | 0.041242 | 0.020756 | 0.008519 | 0.014627 | 0.022947 | 0.012115 | -0.002263 | 0.013715 | -0.026510 | -0.020477 |
| EIC15 | -0.633596 | -0.666075 | 0.208138 | -0.071526 | 0.104283 | 0.143486 | 0.010378 | -0.104057 | -0.093340 | 0.001672 | -0.054746 | -0.031739 | -0.070382 | 0.025540 | 0.011453 | 0.009123 | 0.040620 | 0.025765 | -0.043829 | -0.031441 | -0.043815 | 0.027268 | 0.039718 | -0.029905 | 0.006321 | -0.019953 | 0.015429 | -0.026384 | 0.019752 | -0.008251 | 0.016826 | 0.041532 | 0.040473 | 0.020611 | 0.003483 | 0.020150 | 0.017541 | -0.004869 | 0.024527 | 0.002612 | -0.007654 | -0.024186 | 0.018454 | -0.017361 | 0.018040 | -0.000784 | 0.011579 | 0.009277 | 0.000562 | -0.016764 | 0.007903 | -0.004745 | -0.002340 | 0.020280 | 0.011543 | -0.014574 | 0.015479 | 0.016850 | -0.016769 | 0.005511 | -0.024976 | -0.008548 | -0.020575 | 0.004813 | 0.008353 | 0.009441 | -0.029397 | 0.008707 | 0.009225 | -0.038950 | -0.008979 | 0.010353 | 0.050758 | -0.016323 | 0.020863 | 0.009388 |
| EIC16 | 0.088224 | 0.198343 | -0.198921 | 0.207875 | 0.069853 | -0.022245 | 0.504580 | 0.031966 | -0.450726 | 0.347908 | -0.012682 | -0.087437 | -0.069333 | 0.025002 | 0.020849 | 0.103897 | 0.031851 | 0.269744 | -0.162113 | -0.010147 | 0.117441 | -0.081890 | 0.064485 | -0.004657 | -0.024293 | 0.096154 | -0.057080 | 0.085434 | 0.071760 | 0.032198 | 0.019652 | 0.024408 | -0.136966 | -0.080947 | -0.145690 | 0.021350 | 0.078543 | -0.028841 | -0.042824 | 0.003202 | 0.040751 | 0.037101 | 0.002312 | -0.007059 | 0.000764 | -0.062290 | 0.013463 | -0.031666 | -0.013574 | 0.042778 | 0.014361 | 0.025071 | 0.022594 | 0.021808 | 0.044804 | -0.041105 | -0.026768 | 0.035479 | -0.047118 | -0.020895 | -0.005748 | -0.060042 | 0.007561 | -0.025304 | -0.020600 | -0.001615 | -0.047023 | -0.016262 | 0.011516 | -0.030322 | 0.006365 | -0.030906 | 0.032601 | -0.008314 | 0.027392 | 0.005118 |
| OEDC1 | 0.158587 | 0.286317 | 0.193929 | -0.300687 | 0.306307 | -0.010523 | 0.264578 | 0.001417 | -0.332427 | 0.236503 | -0.003431 | -0.188786 | -0.282120 | -0.151901 | 0.122016 | -0.003112 | -0.029408 | 0.111453 | -0.090687 | 0.078282 | 0.205810 | -0.088224 | 0.074711 | 0.019346 | -0.008246 | 0.019421 | -0.102946 | 0.090488 | 0.028315 | 0.069397 | -0.005050 | -0.136547 | -0.094550 | -0.024437 | 0.062723 | 0.034088 | 0.056406 | 0.098192 | -0.097110 | 0.114295 | -0.006717 | 0.002549 | -0.068650 | -0.005944 | 0.049991 | 0.057289 | 0.022082 | 0.020747 | 0.025556 | -0.025656 | 0.008482 | 0.007948 | -0.091991 | 0.003247 | -0.018265 | 0.028400 | 0.076948 | -0.074547 | 0.030514 | -0.022033 | 0.080612 | 0.056136 | 0.007370 | 0.024848 | 0.010393 | 0.043493 | 0.025316 | -0.003837 | 0.015640 | 0.015629 | 0.006306 | 0.034657 | 0.023931 | 0.042981 | -0.015531 | -0.059574 |
| OEDC2 | 0.283597 | 0.122171 | 0.027345 | 0.113143 | 0.033765 | 0.403760 | 0.232444 | -0.324787 | -0.423637 | 0.217983 | 0.190276 | -0.162002 | -0.044934 | -0.179428 | 0.090257 | 0.070427 | 0.173135 | -0.025230 | -0.238505 | 0.041364 | 0.077999 | 0.013582 | 0.109136 | -0.000293 | 0.039171 | 0.043016 | 0.050531 | -0.008796 | -0.009243 | 0.003091 | 0.041038 | 0.016043 | -0.016361 | -0.047748 | -0.147972 | -0.076942 | -0.068097 | 0.017477 | -0.043772 | -0.069187 | 0.035581 | 0.063424 | 0.012480 | 0.051945 | -0.075061 | -0.023609 | -0.003237 | -0.017617 | 0.027061 | 0.020864 | -0.005343 | 0.000581 | 0.024953 | 0.033214 | 0.024081 | -0.003166 | -0.035165 | 0.043513 | -0.022758 | 0.030331 | -0.009247 | -0.025411 | 0.003245 | -0.041073 | -0.014718 | -0.020234 | 0.008992 | 0.002364 | 0.014538 | 0.037818 | 0.053093 | -0.043321 | -0.045451 | -0.031262 | -0.024395 | 0.048908 |
| OEDC3 | -0.004545 | 0.221706 | -0.385698 | 0.196264 | -0.024181 | -0.070505 | 0.464016 | 0.046535 | -0.403844 | 0.341466 | -0.037916 | 0.032812 | 0.027221 | 0.229849 | -0.074480 | 0.138370 | -0.005560 | 0.293705 | -0.065125 | -0.004778 | 0.008961 | -0.001794 | -0.025181 | 0.009144 | -0.046583 | -0.008490 | -0.022847 | 0.033893 | 0.063218 | 0.010832 | 0.035048 | 0.073532 | -0.043162 | -0.014927 | -0.031791 | 0.020195 | 0.011322 | -0.040930 | 0.050469 | -0.061241 | 0.027555 | -0.010737 | 0.016332 | 0.018050 | -0.030399 | -0.025501 | -0.004351 | -0.005713 | -0.021163 | 0.036331 | 0.020392 | 0.011255 | 0.032271 | 0.017474 | 0.017223 | -0.038951 | -0.013117 | 0.051040 | 0.003266 | 0.009708 | -0.035193 | -0.049741 | -0.001957 | 0.015189 | -0.006771 | -0.014326 | -0.025279 | -0.013681 | -0.029368 | -0.045962 | -0.017893 | -0.005005 | 0.032823 | 0.005112 | 0.030976 | -0.011350 |
| OEDC4 | -0.151518 | 0.211279 | 0.745058 | -0.144393 | -0.241906 | -0.014887 | -0.320917 | -0.234969 | -0.212022 | 0.092551 | -0.125039 | -0.044543 | -0.088007 | 0.052196 | 0.021177 | -0.091775 | 0.028402 | 0.023054 | 0.078996 | -0.022597 | -0.038631 | -0.044937 | -0.052515 | 0.047564 | 0.073589 | 0.034213 | -0.005986 | -0.011401 | 0.008625 | 0.001303 | -0.012562 | -0.000990 | 0.043576 | 0.022201 | -0.021266 | 0.024755 | 0.004206 | 0.011984 | 0.007040 | -0.012602 | -0.010617 | -0.012767 | 0.023754 | -0.022345 | 0.004124 | 0.022436 | 0.019441 | 0.011470 | -0.010333 | 0.022377 | -0.005107 | -0.015996 | 0.000688 | 0.020260 | 0.014433 | 0.009393 | 0.002732 | -0.012032 | -0.010248 | 0.020490 | -0.011439 | 0.005787 | -0.021496 | -0.003285 | -0.003255 | 0.004036 | 0.016092 | 0.005531 | -0.040742 | -0.002557 | -0.002815 | 0.007323 | 0.002329 | -0.015777 | 0.003398 | 0.004075 |
| OEDC5 | -0.216505 | 0.094142 | -0.311413 | 0.284806 | 0.508174 | -0.403875 | -0.163515 | -0.047162 | 0.426889 | -0.232451 | -0.013564 | 0.126234 | 0.163418 | -0.009440 | -0.050787 | -0.007599 | -0.048043 | -0.088458 | 0.070180 | -0.014081 | -0.034536 | 0.007051 | -0.033449 | 0.011112 | -0.049526 | -0.028733 | 0.017238 | -0.023270 | 0.000110 | 0.005254 | -0.019958 | -0.005944 | -0.017764 | 0.015528 | 0.027436 | -0.038796 | -0.011018 | -0.018425 | -0.002248 | 0.009133 | -0.001691 | -0.001137 | 0.003780 | -0.002384 | 0.018115 | -0.022948 | -0.017577 | -0.008462 | 0.005881 | -0.007100 | 0.004139 | 0.011300 | 0.014458 | -0.032322 | -0.012154 | -0.008373 | -0.006254 | 0.002018 | 0.012066 | -0.008509 | 0.002601 | 0.000782 | -0.000843 | -0.009906 | 0.006559 | -0.003188 | -0.000540 | 0.004634 | 0.003084 | 0.008345 | -0.005271 | -0.003241 | -0.015845 | 0.012962 | 0.001902 | -0.004224 |
| OEDC6 | -0.132478 | -0.515936 | 0.331196 | 0.007167 | 0.403693 | 0.421934 | 0.013372 | -0.001681 | -0.159175 | -0.006589 | 0.088749 | -0.156806 | -0.161237 | 0.054232 | -0.007479 | 0.095908 | -0.009616 | -0.063744 | -0.080268 | 0.028695 | -0.078650 | 0.110356 | 0.073018 | -0.129455 | -0.011641 | -0.030630 | 0.006685 | 0.025682 | -0.048825 | -0.066647 | 0.022955 | 0.077933 | 0.098670 | 0.013125 | 0.091281 | 0.102723 | 0.057726 | -0.014008 | 0.090658 | 0.050428 | -0.040032 | -0.036058 | -0.037379 | -0.019403 | 0.004895 | 0.042266 | 0.013899 | 0.027240 | -0.029215 | -0.051278 | -0.022744 | -0.027238 | -0.023397 | 0.022595 | -0.006628 | 0.000460 | 0.025313 | -0.010711 | -0.029558 | -0.035194 | -0.012049 | 0.005949 | -0.004238 | 0.011256 | -0.021720 | 0.010897 | -0.034412 | -0.011429 | 0.021591 | -0.052229 | -0.021503 | 0.018552 | 0.046893 | -0.032836 | 0.009997 | 0.001157 |
| OEDC7 | 0.116879 | 0.413113 | 0.561690 | -0.137970 | -0.227267 | -0.014300 | -0.266803 | -0.167339 | -0.108581 | 0.058373 | -0.020559 | -0.025556 | -0.091543 | 0.096924 | -0.049558 | -0.080285 | 0.053944 | 0.001757 | 0.061321 | 0.035965 | -0.043322 | -0.052590 | -0.120140 | 0.068857 | 0.115166 | 0.092598 | -0.014452 | 0.004372 | 0.011065 | 0.002818 | -0.036914 | -0.006833 | 0.027715 | -0.034938 | -0.047918 | 0.080286 | 0.003461 | -0.007202 | -0.003755 | -0.035956 | -0.031297 | -0.032986 | 0.087861 | -0.026553 | -0.023545 | 0.010670 | 0.052409 | -0.044827 | 0.019754 | 0.063681 | -0.017410 | -0.034510 | -0.007305 | 0.059315 | -0.037876 | 0.105413 | -0.108208 | -0.033705 | -0.013576 | 0.038775 | 0.003020 | 0.035226 | 0.197632 | 0.224125 | 0.108552 | -0.067598 | -0.069414 | -0.038279 | 0.180374 | 0.035404 | 0.004813 | 0.036086 | 0.047593 | 0.009337 | -0.066441 | 0.042980 |
| EC1 | -0.872076 | -0.305202 | 0.133817 | 0.116532 | 0.235691 | 0.036560 | 0.002217 | -0.222465 | -0.054711 | 0.010119 | -0.015687 | -0.023747 | -0.015194 | 0.002973 | -0.005298 | 0.006646 | 0.028187 | -0.009257 | -0.031931 | 0.006545 | -0.012643 | 0.010308 | -0.000851 | 0.014979 | -0.000116 | -0.014589 | 0.010129 | 0.000907 | 0.010401 | -0.004034 | 0.007403 | 0.007301 | 0.001989 | 0.009029 | 0.006302 | -0.012305 | -0.000074 | 0.001084 | -0.002574 | -0.002368 | 0.000277 | 0.000886 | 0.004800 | -0.003538 | 0.004187 | 0.000795 | 0.003705 | -0.003424 | 0.001479 | 0.000539 | 0.001070 | 0.001089 | 0.007459 | 0.001028 | -0.004048 | -0.003157 | 0.001450 | -0.001128 | -0.001165 | 0.000021 | 0.001983 | 0.002673 | 0.000797 | -0.000166 | 0.002686 | 0.000144 | -0.004524 | 0.001522 | -0.002038 | -0.002161 | -0.002073 | -0.000792 | -0.000547 | 0.000219 | 0.000404 | 0.002915 |
| EC2 | 0.857342 | 0.331273 | -0.137725 | -0.258672 | 0.058262 | -0.132794 | -0.119349 | -0.073947 | 0.019103 | -0.102725 | 0.065099 | -0.017620 | 0.019244 | 0.015167 | -0.025962 | 0.028865 | 0.055406 | 0.000633 | -0.013004 | -0.013741 | 0.024616 | -0.003716 | -0.021939 | 0.012631 | -0.014865 | -0.002696 | -0.013706 | -0.006818 | 0.008658 | 0.005207 | 0.006082 | 0.020285 | -0.002282 | -0.009979 | -0.007940 | -0.005787 | -0.011353 | 0.009453 | 0.014485 | 0.017488 | -0.007981 | 0.007089 | -0.005974 | 0.004909 | 0.000798 | -0.009676 | 0.013141 | 0.004614 | 0.008660 | 0.007070 | -0.004927 | -0.000348 | -0.003637 | 0.001804 | -0.003971 | -0.005135 | -0.000710 | 0.003940 | -0.003691 | -0.009621 | 0.009574 | -0.007354 | -0.007019 | 0.007075 | 0.002923 | 0.003880 | -0.003379 | -0.001682 | -0.001612 | -0.005031 | -0.002773 | 0.016103 | -0.006484 | -0.005035 | 0.004963 | -0.000653 |
| EC3 | 0.882511 | 0.367228 | -0.080741 | -0.092746 | 0.119899 | -0.176503 | 0.014520 | -0.042152 | 0.109718 | -0.017342 | -0.029981 | 0.028089 | 0.045171 | -0.031169 | 0.006345 | 0.036479 | 0.008275 | -0.006535 | -0.001539 | -0.001881 | 0.004252 | -0.007853 | 0.012250 | 0.008244 | -0.002499 | 0.004540 | -0.013006 | -0.007025 | 0.006373 | 0.002912 | 0.000909 | 0.000142 | 0.004760 | -0.010023 | 0.005198 | 0.002889 | 0.007861 | -0.004391 | -0.000123 | 0.006231 | -0.001546 | 0.009226 | -0.000384 | 0.000379 | -0.004440 | 0.002573 | 0.003419 | 0.007012 | 0.000277 | -0.002095 | -0.003719 | -0.005941 | -0.007788 | 0.004413 | 0.000901 | 0.004771 | -0.001602 | -0.002218 | -0.005771 | 0.001807 | 0.004845 | -0.000808 | 0.000776 | 0.000503 | 0.001138 | -0.001282 | -0.000983 | -0.007989 | 0.003764 | -0.003018 | 0.000296 | -0.008487 | 0.000903 | -0.000793 | 0.000231 | -0.003270 |
| EC4 | 0.589814 | 0.681804 | 0.188334 | 0.245212 | 0.174988 | -0.095634 | -0.089579 | 0.102298 | 0.100407 | 0.052908 | -0.012773 | 0.018467 | 0.035351 | 0.036937 | -0.006590 | -0.002635 | -0.067846 | 0.002267 | 0.025926 | 0.025145 | -0.007738 | -0.031632 | 0.017199 | -0.027530 | -0.005658 | 0.027788 | -0.003526 | 0.018000 | -0.010719 | 0.014607 | -0.003416 | -0.004171 | -0.006761 | -0.008460 | -0.004817 | 0.020383 | -0.001361 | -0.000644 | -0.013681 | 0.004689 | 0.003295 | -0.006592 | 0.005128 | 0.010674 | -0.008209 | 0.006046 | -0.000086 | -0.004169 | 0.006828 | -0.008410 | 0.010687 | -0.010227 | -0.006227 | 0.006958 | 0.009458 | 0.007406 | 0.000150 | 0.005060 | 0.007677 | 0.002771 | -0.008980 | -0.003689 | -0.000547 | -0.004469 | -0.009280 | 0.008054 | -0.004104 | -0.002908 | 0.003253 | 0.002625 | 0.005627 | -0.010463 | 0.010239 | 0.003640 | 0.000003 | -0.003580 |
| EC5 | -0.800108 | -0.250775 | -0.121198 | 0.355774 | 0.152409 | -0.113931 | 0.117615 | 0.062507 | -0.168338 | 0.114924 | -0.083915 | 0.020310 | -0.053572 | -0.067295 | 0.028131 | -0.043633 | -0.079712 | 0.064690 | 0.052887 | 0.007393 | -0.035256 | -0.012735 | -0.033582 | -0.001034 | 0.023158 | -0.000231 | 0.017368 | -0.002486 | -0.002366 | -0.007640 | -0.021549 | -0.018398 | -0.016448 | 0.022098 | 0.002807 | 0.005555 | 0.023243 | -0.012814 | 0.008304 | -0.033582 | 0.007855 | -0.015305 | 0.002417 | -0.015868 | 0.014703 | -0.004202 | -0.024718 | -0.004400 | -0.023135 | 0.008910 | -0.010581 | 0.016945 | 0.012074 | -0.026834 | -0.007871 | -0.000099 | 0.001881 | 0.001384 | 0.005693 | 0.014768 | -0.018043 | 0.021574 | 0.021409 | -0.009324 | 0.006510 | -0.023874 | 0.019455 | 0.001004 | -0.013737 | 0.009548 | -0.000601 | -0.003066 | -0.005113 | 0.002646 | -0.013530 | 0.008175 |
| EC6 | -0.829527 | -0.096490 | -0.279134 | 0.262724 | 0.101999 | -0.036605 | -0.014701 | 0.100688 | -0.120840 | 0.151650 | -0.008377 | -0.066592 | -0.013278 | -0.024730 | 0.025218 | -0.064910 | -0.055841 | -0.000017 | 0.091269 | 0.027767 | 0.038941 | 0.054025 | 0.023217 | 0.025308 | -0.006983 | -0.011935 | -0.046096 | 0.047884 | -0.057344 | 0.030385 | -0.006153 | -0.031622 | -0.010592 | 0.038895 | -0.012929 | 0.014415 | 0.008015 | -0.005637 | 0.020158 | 0.025014 | -0.022463 | -0.026896 | -0.033869 | -0.032339 | 0.019459 | -0.002764 | -0.043750 | 0.021716 | -0.029118 | 0.020133 | -0.005861 | 0.014822 | 0.045976 | -0.045806 | -0.004324 | -0.017235 | -0.034807 | -0.021039 | 0.001973 | 0.015058 | 0.010220 | -0.017224 | -0.015672 | -0.006573 | -0.015470 | -0.017107 | 0.008196 | 0.045287 | 0.012591 | -0.006516 | 0.022092 | 0.031300 | -0.004183 | -0.026222 | -0.005978 | -0.004881 |
| EC7 | -0.856436 | -0.473389 | 0.063023 | 0.039436 | -0.007217 | 0.124515 | 0.028191 | -0.101950 | -0.047272 | -0.015753 | 0.007273 | -0.028372 | -0.026978 | 0.009664 | -0.005098 | -0.016492 | 0.030410 | -0.020048 | -0.027478 | -0.009740 | -0.013590 | 0.013577 | -0.013659 | 0.012027 | -0.002483 | -0.011184 | 0.012782 | -0.005801 | 0.013164 | -0.010680 | 0.000505 | 0.001342 | -0.002100 | 0.008880 | 0.003342 | -0.017665 | -0.002455 | 0.004232 | 0.001749 | -0.004282 | 0.002369 | -0.000895 | 0.003299 | -0.004165 | 0.007004 | -0.002900 | 0.004079 | -0.002901 | 0.002090 | -0.000873 | 0.000105 | 0.002045 | 0.005818 | 0.002928 | -0.000359 | -0.004619 | 0.002180 | -0.002000 | -0.002744 | -0.005306 | 0.002400 | 0.001853 | -0.001958 | 0.001121 | 0.004425 | 0.001462 | -0.004700 | 0.001851 | -0.001189 | -0.001519 | -0.005844 | 0.001359 | -0.002144 | 0.003302 | 0.002847 | 0.000926 |
| EC8 | -0.783963 | -0.511469 | 0.190020 | -0.095992 | -0.013885 | 0.179899 | 0.031553 | -0.161779 | -0.071430 | -0.018094 | 0.021137 | -0.007879 | -0.033517 | 0.012604 | 0.004508 | 0.027596 | 0.049734 | -0.015374 | -0.054786 | -0.000265 | 0.007088 | 0.022972 | 0.025092 | -0.003821 | 0.004522 | -0.017999 | 0.016907 | -0.007267 | 0.005067 | -0.007806 | 0.010779 | 0.007564 | 0.018923 | -0.002484 | 0.008529 | -0.008460 | -0.006442 | -0.000358 | -0.010062 | -0.004096 | 0.000472 | 0.008302 | 0.004779 | 0.005412 | -0.010075 | 0.008361 | 0.006114 | -0.005785 | 0.004802 | -0.003485 | 0.004491 | 0.000180 | -0.007678 | 0.012784 | -0.003140 | 0.001033 | 0.008007 | -0.000436 | -0.000182 | -0.001198 | 0.002351 | 0.001004 | 0.000000 | 0.003534 | 0.001294 | 0.004639 | -0.001601 | -0.003149 | 0.000045 | 0.001308 | -0.000863 | -0.003438 | 0.001368 | 0.001484 | 0.000549 | 0.001523 |
| SEC1 | -0.798322 | -0.423069 | -0.071075 | -0.137206 | 0.143613 | 0.202477 | -0.009746 | -0.012510 | 0.031804 | -0.047497 | 0.047249 | -0.016327 | -0.062053 | 0.058141 | -0.005137 | 0.143763 | 0.009834 | -0.074225 | -0.005997 | 0.010854 | -0.063233 | -0.006616 | 0.032032 | -0.061308 | 0.003609 | 0.058943 | 0.014269 | 0.003560 | -0.032205 | -0.002104 | -0.011818 | -0.013207 | -0.003016 | 0.010247 | 0.070467 | 0.087950 | 0.044163 | -0.037268 | 0.020592 | 0.015238 | 0.026956 | -0.002486 | 0.001717 | -0.039509 | 0.034223 | -0.020678 | 0.015048 | -0.023411 | -0.033961 | 0.026391 | -0.022043 | 0.008065 | -0.003185 | 0.005271 | -0.016411 | -0.013423 | 0.024192 | 0.013169 | -0.011610 | -0.011050 | -0.011114 | 0.002495 | -0.001647 | 0.014832 | 0.009944 | -0.015802 | -0.020125 | 0.014343 | -0.017561 | 0.014238 | -0.028405 | 0.009470 | -0.011301 | 0.005149 | 0.042401 | 0.014739 |
| SEC2 | -0.162975 | 0.653287 | -0.667049 | -0.018070 | 0.115272 | 0.041691 | 0.005132 | -0.158486 | -0.165568 | -0.001941 | 0.081064 | -0.017382 | -0.002615 | -0.060686 | 0.004708 | -0.024239 | -0.057367 | 0.001698 | -0.016949 | 0.042741 | -0.000953 | 0.004658 | 0.012566 | 0.030321 | 0.039860 | -0.038461 | 0.018653 | 0.002645 | -0.034534 | 0.004401 | 0.003032 | -0.007574 | -0.015170 | 0.001160 | -0.014217 | -0.023213 | -0.009905 | 0.007245 | -0.016193 | -0.018883 | 0.003107 | 0.013553 | 0.003911 | 0.013173 | -0.016237 | -0.002305 | -0.022265 | 0.007097 | 0.007014 | -0.008539 | 0.019590 | 0.001662 | 0.014924 | -0.000178 | 0.000463 | -0.000523 | -0.016026 | -0.006136 | 0.015832 | 0.018775 | -0.007963 | 0.009421 | -0.006246 | -0.009288 | 0.000042 | 0.000684 | 0.008458 | 0.003827 | 0.009635 | 0.001825 | 0.020133 | -0.005910 | -0.003092 | -0.003466 | -0.014533 | 0.002344 |
| SEC3 | -0.808769 | 0.275190 | -0.303652 | 0.061605 | 0.103988 | 0.155852 | 0.051321 | -0.016155 | -0.048506 | -0.141290 | -0.115766 | -0.130656 | -0.031075 | 0.048966 | -0.006362 | -0.037096 | -0.025302 | -0.023412 | -0.013732 | 0.028300 | -0.032681 | 0.017282 | 0.059292 | -0.014505 | -0.038955 | 0.013335 | 0.001870 | -0.014709 | -0.010577 | -0.026527 | 0.003722 | -0.049478 | 0.002969 | 0.008120 | 0.028211 | 0.040127 | 0.030201 | -0.016249 | -0.024669 | -0.005980 | 0.016592 | -0.004484 | 0.015015 | -0.006950 | 0.021801 | 0.004766 | -0.015327 | -0.014833 | -0.013680 | 0.007053 | 0.027742 | 0.013523 | 0.022347 | 0.048136 | -0.034485 | -0.034699 | 0.013921 | -0.020405 | -0.003703 | -0.003747 | -0.031351 | -0.004837 | -0.017022 | -0.041016 | 0.037522 | -0.034276 | -0.035096 | 0.025463 | 0.003435 | 0.058216 | 0.022950 | -0.007594 | -0.070922 | 0.009129 | 0.065900 | 0.079935 |
| SEC4 | -0.131522 | 0.856287 | -0.437880 | -0.125099 | 0.096484 | -0.013586 | 0.021455 | -0.098209 | -0.066960 | -0.054879 | 0.028508 | -0.013639 | -0.017351 | 0.011342 | -0.020951 | -0.060726 | -0.052236 | 0.031765 | -0.003266 | -0.008890 | 0.000078 | -0.002589 | 0.025056 | 0.000427 | 0.020881 | -0.012797 | 0.011587 | -0.001190 | -0.010831 | -0.006440 | -0.006973 | 0.001630 | -0.004755 | -0.003338 | 0.010160 | 0.003221 | 0.008539 | -0.002214 | 0.001795 | 0.004232 | 0.000103 | 0.006737 | 0.002682 | -0.001346 | 0.001378 | -0.000438 | -0.001644 | 0.002713 | -0.003030 | -0.005541 | 0.001314 | -0.002798 | 0.002966 | 0.005931 | -0.001833 | -0.003969 | -0.001176 | -0.000065 | 0.000472 | 0.005914 | -0.003832 | 0.004291 | -0.003518 | -0.002297 | -0.001784 | 0.000600 | 0.004031 | -0.000246 | 0.006126 | -0.004316 | 0.008255 | -0.004856 | 0.002909 | -0.001271 | -0.004239 | -0.002297 |
| SEC5 | -0.408705 | -0.682478 | -0.401058 | 0.078337 | 0.109626 | 0.198070 | -0.046942 | -0.114767 | -0.145374 | 0.093843 | 0.153411 | 0.012297 | -0.008595 | -0.099897 | 0.042506 | 0.168315 | 0.001601 | -0.096927 | -0.025708 | 0.092335 | -0.036782 | 0.004358 | -0.013264 | 0.016163 | 0.046249 | -0.009358 | 0.022705 | 0.012558 | -0.061809 | 0.023420 | 0.009030 | -0.013842 | -0.020891 | 0.013046 | -0.002044 | 0.002750 | -0.009340 | -0.004273 | -0.012733 | -0.029273 | 0.019542 | 0.012170 | 0.000172 | 0.000943 | -0.013090 | -0.018293 | -0.023222 | -0.004356 | -0.001888 | 0.010752 | 0.011306 | 0.010233 | 0.014220 | -0.018036 | 0.000588 | 0.004822 | -0.013433 | 0.002666 | 0.020304 | 0.016712 | -0.007799 | 0.012057 | -0.002228 | 0.006792 | 0.001439 | -0.002718 | 0.002632 | 0.011188 | -0.006157 | 0.007071 | -0.002848 | 0.005872 | -0.002334 | -0.002752 | -0.005055 | 0.000014 |
| AFC1 | -0.071161 | 0.003486 | -0.431908 | 0.340273 | -0.148519 | -0.029757 | 0.328777 | 0.046434 | -0.367326 | 0.155507 | -0.055647 | 0.106258 | 0.187087 | 0.417965 | -0.139608 | 0.263246 | -0.001168 | 0.208711 | 0.075255 | 0.041827 | 0.056047 | -0.014810 | -0.042556 | 0.076475 | -0.018999 | -0.041278 | 0.029836 | -0.026628 | -0.043086 | -0.032488 | -0.025986 | -0.005712 | 0.027088 | 0.064866 | 0.028300 | -0.019983 | -0.011285 | 0.048977 | 0.009764 | 0.020723 | 0.010466 | 0.010376 | -0.010948 | 0.004587 | 0.013143 | -0.004920 | -0.000559 | 0.022672 | 0.013761 | -0.023252 | 0.006510 | -0.007886 | -0.010012 | -0.003494 | 0.017438 | 0.006935 | -0.000603 | 0.003779 | -0.019267 | -0.004430 | 0.022711 | 0.012472 | 0.022775 | -0.003215 | 0.006292 | -0.000894 | 0.020151 | -0.015229 | -0.002975 | 0.003093 | 0.016983 | 0.003278 | -0.014220 | 0.000549 | -0.002780 | 0.013673 |
| AFC2 | -0.073515 | 0.007202 | -0.435539 | 0.348472 | -0.144284 | -0.036647 | 0.339141 | 0.045249 | -0.368689 | 0.153752 | -0.055085 | 0.104791 | 0.185722 | 0.412604 | -0.135567 | 0.250488 | -0.001161 | 0.207910 | 0.070488 | 0.039838 | 0.052934 | -0.010318 | -0.039633 | 0.076030 | -0.016270 | -0.041041 | 0.027634 | -0.025664 | -0.041669 | -0.029439 | -0.024990 | -0.007165 | 0.026860 | 0.059176 | 0.020954 | -0.018138 | -0.010372 | 0.045450 | 0.009976 | 0.018146 | 0.008788 | 0.010161 | -0.010303 | 0.006475 | 0.009157 | -0.000998 | -0.000144 | 0.018804 | 0.010717 | -0.020226 | 0.007452 | -0.005988 | -0.006672 | -0.002611 | 0.016420 | 0.006519 | 0.001903 | 0.003062 | -0.014341 | -0.001182 | 0.018923 | 0.012908 | 0.017673 | -0.001847 | 0.004352 | -0.000575 | 0.016055 | -0.012088 | -0.002457 | 0.000677 | 0.014567 | 0.003234 | -0.011694 | -0.000413 | -0.001432 | 0.010258 |
| AFC3 | -0.050887 | -0.021201 | -0.407765 | 0.318390 | -0.144080 | -0.013796 | 0.309116 | 0.047478 | -0.346225 | 0.162542 | -0.052098 | 0.108979 | 0.186481 | 0.422639 | -0.156769 | 0.267830 | 0.012161 | 0.215853 | 0.077729 | 0.049437 | 0.071658 | -0.026343 | -0.050854 | 0.072960 | -0.028615 | -0.037356 | 0.035148 | -0.020929 | -0.054350 | -0.045080 | -0.032112 | 0.009314 | 0.030571 | 0.076352 | 0.045529 | -0.028553 | -0.015077 | 0.060459 | 0.010540 | 0.027361 | 0.015961 | 0.010611 | -0.015029 | -0.002767 | 0.027164 | -0.013422 | 0.000934 | 0.033335 | 0.027610 | -0.037090 | 0.003383 | -0.012589 | -0.019945 | -0.000880 | 0.016848 | 0.008662 | -0.010672 | 0.007460 | -0.035467 | -0.016228 | 0.035523 | 0.015178 | 0.039848 | -0.006727 | 0.017326 | -0.003699 | 0.036863 | -0.024039 | -0.004136 | 0.009623 | 0.027055 | 0.008473 | -0.028112 | 0.003630 | -0.005475 | 0.031494 |
| AFC4 | -0.248827 | 0.245547 | 0.776618 | 0.266456 | 0.053994 | -0.219612 | 0.193238 | 0.041721 | -0.129684 | 0.157915 | -0.131207 | 0.127810 | -0.001408 | -0.004870 | 0.024665 | 0.005261 | -0.101809 | 0.044747 | -0.017717 | -0.000454 | -0.012281 | 0.044740 | -0.023800 | -0.044463 | -0.037701 | -0.002370 | -0.000012 | 0.021912 | 0.023055 | -0.003706 | 0.015469 | -0.000065 | -0.012906 | -0.036898 | -0.005748 | 0.006272 | -0.008653 | -0.055371 | -0.008714 | -0.011893 | -0.027405 | -0.008356 | 0.014088 | 0.003067 | -0.000478 | 0.003366 | 0.001277 | -0.024797 | 0.004896 | 0.005796 | -0.028629 | -0.009315 | -0.021039 | -0.005809 | -0.047834 | 0.001199 | 0.001708 | 0.004967 | 0.021039 | -0.001336 | -0.002876 | -0.004565 | -0.024261 | 0.018801 | 0.005993 | 0.007161 | 0.015661 | 0.012091 | -0.008886 | -0.000410 | 0.013094 | -0.002354 | 0.006230 | 0.001897 | -0.010717 | -0.006192 |
| AFC5 | -0.151384 | 0.159671 | 0.856535 | 0.214428 | 0.124550 | -0.190965 | 0.209343 | 0.046386 | -0.097902 | 0.111761 | -0.105852 | 0.095845 | 0.001802 | -0.015637 | 0.020005 | -0.020357 | -0.086156 | 0.044104 | -0.021874 | -0.000047 | -0.011713 | 0.041350 | -0.019010 | -0.045003 | -0.028836 | 0.005121 | 0.000763 | 0.015395 | 0.016646 | -0.006265 | 0.014210 | -0.000164 | -0.011615 | -0.030752 | -0.007340 | 0.015184 | -0.002770 | -0.042284 | -0.003111 | -0.012325 | -0.019629 | -0.009950 | 0.008909 | 0.003990 | -0.002563 | -0.000639 | -0.001290 | -0.017340 | -0.000407 | 0.001421 | -0.019739 | -0.006422 | -0.017837 | -0.004873 | -0.035904 | -0.003617 | -0.000401 | 0.006286 | 0.016006 | 0.000636 | -0.003187 | -0.001246 | -0.012201 | 0.019982 | 0.000615 | 0.004460 | 0.018451 | 0.012789 | -0.007891 | -0.011372 | 0.018757 | -0.008134 | 0.006040 | 0.007940 | -0.012993 | -0.005420 |
| AFC6 | 0.052502 | -0.218000 | 0.013635 | 0.443819 | -0.076688 | -0.248837 | 0.357922 | 0.065627 | -0.357454 | 0.235249 | -0.182247 | 0.116341 | 0.064780 | 0.159025 | -0.046149 | 0.134040 | -0.075883 | 0.168558 | 0.066499 | -0.008338 | 0.016803 | 0.079223 | 0.013979 | 0.020940 | -0.007004 | -0.074676 | -0.002350 | 0.017397 | -0.014463 | -0.020201 | 0.027374 | -0.002488 | 0.003139 | -0.029223 | -0.022506 | -0.015685 | -0.017435 | -0.119701 | -0.027202 | -0.043928 | -0.031771 | 0.002635 | 0.020170 | 0.002414 | 0.034033 | 0.042520 | 0.026509 | -0.094668 | 0.032262 | 0.024332 | -0.086374 | -0.006003 | -0.031742 | -0.022998 | -0.114522 | 0.058427 | 0.034940 | -0.024742 | 0.120556 | 0.006889 | -0.047894 | 0.019270 | -0.182392 | -0.014257 | 0.050423 | 0.022282 | -0.056953 | 0.029170 | 0.067209 | 0.102231 | -0.075048 | 0.080138 | -0.003485 | -0.067673 | -0.006354 | -0.025366 |
| VC1 | -0.556787 | 0.443066 | -0.594467 | 0.262797 | 0.011987 | 0.031566 | 0.048413 | -0.083970 | -0.061449 | 0.024392 | 0.002054 | -0.046452 | 0.013095 | -0.028553 | -0.036287 | -0.020859 | -0.032995 | 0.068125 | 0.010485 | -0.069026 | -0.032849 | -0.010738 | 0.037570 | 0.047599 | -0.013232 | -0.019117 | -0.014514 | 0.000313 | -0.002987 | -0.001980 | 0.009012 | 0.046520 | -0.039575 | 0.004638 | 0.002948 | 0.004788 | 0.011022 | -0.032183 | -0.003439 | 0.021242 | -0.000154 | -0.015177 | 0.003139 | -0.022467 | -0.019829 | 0.007986 | 0.012319 | -0.002400 | -0.010899 | 0.011228 | 0.011222 | 0.017334 | -0.012120 | 0.021009 | -0.034658 | -0.048936 | 0.000005 | 0.015063 | 0.003995 | 0.007914 | 0.013093 | 0.009204 | 0.032629 | 0.039838 | -0.012439 | -0.026584 | 0.028685 | 0.027605 | -0.038680 | -0.022966 | 0.056022 | -0.009096 | -0.002962 | 0.008171 | -0.015176 | -0.024077 |
| VC2 | -0.349659 | 0.206769 | 0.588275 | -0.136562 | 0.163341 | -0.097126 | 0.004623 | -0.074646 | -0.055957 | 0.173662 | 0.042849 | 0.234509 | 0.016605 | -0.014698 | 0.039008 | -0.027381 | 0.026454 | 0.033819 | -0.086666 | 0.084277 | 0.026883 | 0.029141 | -0.210434 | -0.087566 | -0.105580 | 0.085382 | -0.122077 | -0.035285 | 0.068236 | -0.023024 | -0.057196 | 0.015652 | 0.183400 | -0.030063 | -0.047008 | 0.096163 | -0.059021 | 0.167729 | 0.024882 | 0.090105 | 0.125551 | 0.121174 | 0.027731 | -0.016815 | -0.077439 | -0.038021 | -0.038035 | 0.036901 | -0.120832 | -0.067208 | 0.047651 | 0.080824 | 0.026458 | -0.043289 | 0.024857 | -0.049347 | 0.037313 | -0.047566 | 0.061881 | 0.038576 | -0.004993 | -0.023624 | -0.000157 | 0.018574 | 0.032837 | 0.008743 | -0.038044 | 0.065394 | 0.049783 | 0.015911 | -0.025283 | -0.031326 | -0.008324 | -0.042857 | 0.041567 | 0.005658 |
| VC3 | 0.349535 | -0.301082 | 0.832113 | -0.151395 | 0.149819 | -0.146869 | -0.010215 | 0.016561 | -0.021030 | -0.029842 | -0.014385 | -0.013675 | -0.032288 | 0.010982 | 0.032868 | 0.019040 | 0.027107 | -0.056070 | -0.028020 | 0.032252 | 0.012073 | 0.009195 | -0.004175 | -0.015864 | 0.032870 | -0.005269 | 0.038609 | -0.022093 | -0.001945 | -0.003683 | -0.008070 | -0.015407 | 0.001602 | -0.001449 | 0.009420 | -0.017457 | 0.010053 | 0.014629 | 0.012156 | -0.017221 | -0.016009 | -0.007087 | -0.000091 | 0.019148 | 0.029421 | -0.015136 | -0.000003 | 0.007407 | 0.014935 | 0.000913 | -0.007625 | -0.017370 | -0.004151 | 0.000768 | 0.015032 | 0.006743 | -0.016672 | 0.016219 | -0.025579 | -0.014541 | 0.000143 | -0.001186 | -0.001102 | -0.004402 | 0.006298 | 0.004034 | 0.008189 | -0.021250 | -0.007963 | -0.008812 | -0.002700 | -0.008286 | -0.004085 | -0.000131 | 0.016008 | 0.007868 |
| VC4 | 0.363673 | -0.128034 | -0.820907 | 0.300061 | 0.072801 | -0.044036 | 0.080285 | -0.055685 | -0.051778 | 0.024771 | -0.046889 | 0.021396 | 0.064840 | 0.063784 | -0.031976 | 0.066296 | 0.022436 | 0.010991 | 0.049383 | 0.008661 | 0.007957 | 0.014601 | 0.016094 | 0.011291 | 0.006144 | -0.009292 | 0.008819 | 0.050006 | -0.008857 | 0.014812 | 0.020881 | -0.030212 | -0.011937 | -0.001660 | -0.015974 | -0.008322 | -0.017230 | -0.051206 | -0.015393 | -0.030892 | -0.017885 | 0.000278 | -0.006148 | -0.003192 | -0.002009 | 0.025002 | 0.002657 | -0.026998 | 0.029448 | 0.007145 | -0.021300 | -0.018926 | 0.021097 | -0.010734 | -0.005645 | 0.057697 | 0.014137 | -0.026424 | 0.022918 | 0.008897 | -0.016797 | 0.000275 | -0.050031 | -0.036803 | 0.003680 | 0.022997 | -0.041392 | -0.008270 | 0.038928 | 0.029045 | -0.054576 | 0.029767 | 0.017174 | -0.001930 | -0.015909 | 0.012485 |
| ANC1 | -0.108703 | 0.232714 | 0.297272 | 0.189119 | 0.040130 | 0.127260 | -0.202693 | 0.113318 | 0.003283 | -0.071195 | 0.008165 | -0.055857 | -0.010700 | 0.021634 | -0.035426 | -0.015238 | -0.064353 | -0.057295 | 0.106364 | 0.098119 | 0.034186 | 0.107971 | -0.023785 | -0.119500 | -0.014621 | 0.028418 | 0.040036 | -0.040711 | -0.041434 | -0.053945 | -0.044574 | -0.029279 | 0.063367 | 0.087816 | 0.078240 | 0.034236 | 0.273974 | -0.096935 | -0.004605 | 0.132066 | 0.227691 | 0.134732 | 0.122456 | 0.028031 | -0.059542 | 0.351986 | -0.015169 | 0.114995 | 0.243102 | 0.318437 | -0.119666 | 0.167201 | 0.092872 | -0.058825 | 0.056540 | -0.077878 | -0.019343 | 0.167587 | 0.011697 | -0.009751 | 0.077182 | -0.127380 | -0.031813 | 0.022903 | 0.016517 | 0.049497 | 0.072718 | 0.019605 | 0.098159 | -0.067650 | 0.005774 | 0.048788 | -0.034783 | 0.009971 | -0.012788 | -0.009570 |
| ANC2 | -0.346680 | 0.155503 | 0.727745 | 0.312886 | -0.129131 | 0.013044 | 0.096065 | -0.194701 | -0.115125 | -0.036404 | -0.010729 | 0.081117 | 0.084954 | -0.113262 | 0.004244 | 0.005462 | 0.092215 | 0.018955 | -0.081841 | -0.126574 | -0.030353 | 0.073994 | -0.030381 | 0.051590 | 0.033720 | 0.011822 | 0.067303 | -0.080584 | 0.079309 | -0.025741 | -0.042640 | -0.064005 | -0.015754 | -0.014116 | 0.005278 | 0.014144 | 0.046597 | -0.007168 | -0.007965 | -0.040043 | 0.017132 | 0.004903 | -0.034454 | 0.019370 | 0.003456 | 0.017148 | -0.006172 | 0.053882 | -0.037209 | -0.007812 | 0.009400 | -0.023733 | 0.023006 | -0.027492 | 0.020531 | 0.006587 | -0.021045 | -0.009286 | 0.009333 | 0.022571 | -0.017954 | -0.006213 | 0.013192 | -0.034338 | -0.033094 | 0.014355 | -0.001878 | -0.014878 | 0.007179 | 0.009571 | -0.027568 | -0.046033 | 0.027692 | -0.001084 | -0.029837 | 0.008914 |
| ANC3 | 0.017305 | 0.081543 | 0.417267 | 0.375448 | -0.046030 | -0.026732 | 0.031380 | -0.017964 | -0.022413 | -0.063145 | -0.088549 | 0.086298 | 0.016194 | -0.103234 | -0.001899 | 0.054962 | -0.077243 | 0.017812 | -0.125724 | 0.080890 | -0.166739 | -0.061740 | 0.160322 | 0.059916 | 0.006794 | 0.043345 | 0.075549 | 0.053078 | 0.004844 | -0.040436 | -0.178817 | -0.057353 | 0.020537 | 0.062780 | 0.026059 | 0.019244 | -0.193930 | -0.012584 | -0.007327 | 0.203265 | 0.044422 | -0.061474 | 0.127959 | 0.181372 | 0.151509 | -0.118094 | 0.377292 | -0.132479 | -0.050345 | 0.000093 | -0.084614 | 0.074496 | 0.067430 | 0.006609 | 0.119150 | 0.034048 | 0.149713 | 0.070957 | 0.139465 | -0.022409 | -0.100796 | -0.126729 | 0.001657 | 0.034093 | -0.081189 | -0.027300 | 0.104510 | -0.038712 | 0.014584 | -0.011080 | 0.003718 | -0.038759 | 0.000298 | -0.004428 | -0.101413 | 0.045960 |
| ANC4 | -0.096712 | 0.384504 | 0.545345 | 0.435701 | 0.133401 | 0.305288 | -0.321548 | 0.099903 | -0.045540 | -0.041483 | 0.021523 | -0.074970 | -0.041356 | 0.129989 | -0.045471 | -0.058056 | -0.111696 | -0.040951 | 0.098407 | 0.046589 | 0.014721 | 0.025657 | -0.051104 | -0.087807 | -0.016995 | 0.006104 | -0.016791 | 0.051066 | -0.050249 | -0.018651 | 0.002085 | 0.039959 | -0.017244 | -0.011600 | -0.025213 | 0.048692 | -0.035474 | 0.001449 | -0.034509 | 0.014433 | -0.006412 | -0.029399 | 0.027048 | 0.006382 | -0.027037 | -0.011873 | -0.010562 | -0.051716 | 0.020190 | -0.046373 | 0.045056 | -0.022470 | -0.014213 | 0.022319 | 0.007249 | 0.029208 | -0.005063 | -0.027995 | 0.001800 | -0.040924 | -0.001552 | 0.022301 | 0.020148 | -0.027483 | -0.014293 | 0.032498 | -0.024940 | 0.049288 | -0.032215 | 0.006323 | 0.038465 | -0.004878 | 0.006621 | -0.025934 | 0.002048 | 0.002507 |
| ANC5 | -0.461906 | -0.577631 | 0.231615 | -0.117636 | 0.086183 | -0.019432 | -0.045225 | 0.123939 | 0.127241 | -0.048365 | -0.008525 | 0.058270 | -0.071454 | 0.053149 | -0.061958 | 0.069716 | -0.068404 | -0.036027 | -0.066940 | 0.085655 | 0.005098 | -0.088877 | 0.056223 | 0.103410 | 0.054156 | 0.011547 | -0.073078 | -0.064021 | 0.046899 | 0.019410 | -0.021067 | -0.040456 | 0.079507 | -0.051530 | -0.003051 | -0.065777 | -0.013894 | -0.012961 | 0.096999 | -0.040864 | -0.027301 | 0.081558 | -0.148953 | -0.060012 | -0.004811 | -0.001742 | -0.026686 | -0.070116 | -0.054662 | 0.155726 | -0.010659 | -0.194920 | 0.017218 | 0.065803 | 0.011969 | -0.138445 | 0.032703 | 0.017857 | 0.057602 | -0.080580 | -0.068474 | 0.020015 | 0.080872 | -0.120270 | 0.107923 | 0.093803 | 0.122440 | 0.100164 | 0.079962 | -0.003159 | 0.015120 | -0.010074 | 0.101389 | -0.021743 | -0.051839 | -0.015258 |
| ANC6 | -0.350706 | -0.597758 | 0.370619 | -0.041485 | 0.031386 | -0.146287 | -0.034080 | 0.113321 | 0.147465 | -0.067184 | -0.027100 | 0.082820 | -0.072896 | 0.031983 | -0.038107 | 0.053754 | -0.048872 | -0.021275 | 0.036906 | 0.140198 | 0.029646 | -0.038407 | 0.156654 | 0.102579 | 0.024628 | -0.019428 | 0.033536 | -0.000202 | -0.022416 | 0.048385 | -0.023663 | 0.079717 | 0.008001 | -0.036525 | 0.005136 | 0.008621 | 0.053936 | 0.031536 | -0.097893 | -0.020950 | -0.092985 | -0.033059 | 0.126286 | 0.032303 | -0.088490 | 0.038134 | -0.085430 | -0.006739 | -0.063674 | -0.082198 | -0.087649 | -0.019174 | -0.112808 | -0.042103 | 0.008758 | -0.088107 | 0.044328 | -0.067947 | -0.003213 | 0.149713 | 0.022018 | -0.148225 | 0.012802 | -0.087044 | 0.023884 | -0.101679 | 0.041322 | -0.015151 | 0.020161 | -0.075539 | -0.053774 | 0.069127 | 0.029303 | 0.108598 | -0.032580 | 0.015521 |
| ANC7 | -0.005019 | 0.234172 | 0.634058 | 0.500044 | -0.003518 | 0.012896 | 0.050443 | -0.110978 | 0.153292 | -0.073633 | -0.013549 | 0.076410 | 0.172567 | -0.090758 | 0.001199 | 0.118190 | 0.099011 | 0.051543 | -0.195046 | -0.116342 | -0.061525 | -0.060379 | -0.067768 | 0.084313 | 0.058522 | 0.037996 | 0.038240 | -0.060204 | 0.068388 | 0.018924 | 0.000225 | -0.037011 | 0.025047 | -0.039618 | 0.010206 | 0.070758 | 0.074358 | 0.023774 | 0.030682 | 0.000345 | -0.053186 | 0.016373 | -0.083498 | 0.009620 | -0.030051 | -0.023144 | 0.030247 | 0.047406 | 0.009460 | 0.000626 | 0.027413 | -0.031378 | -0.015448 | -0.006800 | -0.006377 | 0.026686 | -0.013617 | -0.007965 | -0.035130 | -0.013233 | 0.037447 | -0.007377 | -0.066212 | 0.028915 | 0.026694 | -0.044672 | 0.007253 | -0.021328 | 0.013077 | -0.004243 | -0.051798 | -0.019338 | -0.018449 | 0.013821 | -0.026026 | -0.029730 |
| ANC8 | -0.539504 | -0.632169 | 0.260706 | 0.048058 | 0.044453 | -0.255530 | 0.010853 | 0.191581 | 0.112679 | -0.041412 | -0.045746 | 0.026708 | -0.065823 | -0.007593 | 0.016565 | 0.082244 | -0.102260 | -0.046359 | -0.008215 | 0.068918 | 0.022098 | -0.082592 | 0.041121 | 0.112770 | 0.039353 | 0.039699 | -0.054658 | -0.029253 | -0.025911 | 0.031328 | -0.008348 | -0.011043 | 0.016629 | -0.052693 | 0.009685 | -0.009790 | -0.005100 | -0.014131 | 0.025612 | 0.055223 | -0.006713 | 0.017488 | -0.036417 | 0.017349 | 0.016032 | -0.032036 | 0.016059 | -0.006072 | -0.004830 | 0.018034 | 0.039170 | -0.014122 | -0.010662 | 0.006481 | -0.000794 | 0.009283 | -0.006746 | 0.022844 | 0.020210 | -0.022080 | -0.002315 | -0.018377 | -0.026026 | 0.004345 | -0.001982 | -0.037479 | -0.004301 | 0.008184 | 0.023298 | 0.005452 | 0.030417 | 0.019654 | -0.041818 | 0.038521 | 0.053994 | 0.011522 |
| ANC9 | 0.019460 | 0.056691 | 0.386790 | 0.205338 | -0.003572 | 0.270618 | -0.320027 | 0.036883 | -0.262376 | 0.097786 | -0.063824 | -0.166448 | -0.158938 | 0.096860 | -0.033903 | -0.199022 | -0.215777 | -0.029968 | 0.196031 | 0.044025 | -0.037834 | 0.114865 | -0.005098 | -0.113667 | -0.055751 | -0.103380 | -0.155857 | 0.026653 | -0.071853 | 0.053962 | 0.174047 | -0.024528 | -0.078327 | 0.051686 | -0.084951 | -0.084523 | -0.194025 | 0.109277 | -0.016169 | 0.002584 | -0.018265 | -0.001631 | -0.106112 | -0.106107 | 0.072189 | -0.038688 | 0.032012 | 0.074952 | -0.027472 | 0.018047 | -0.062165 | 0.000297 | 0.040228 | -0.004411 | 0.036190 | -0.046127 | 0.007190 | 0.020300 | -0.049318 | 0.020940 | 0.065908 | -0.025518 | -0.032774 | 0.041358 | 0.016098 | 0.004001 | -0.021519 | -0.037116 | -0.000980 | -0.106012 | -0.040336 | 0.094939 | 0.000340 | -0.050429 | -0.025376 | -0.001562 |
| ANC10 | -0.276009 | -0.372633 | 0.292425 | 0.008796 | 0.252449 | -0.011197 | -0.126974 | 0.332278 | 0.354381 | -0.140793 | 0.017603 | 0.001448 | -0.190658 | 0.164666 | -0.070813 | 0.174794 | -0.256634 | -0.054711 | -0.089450 | 0.186664 | 0.101334 | -0.098843 | 0.068861 | 0.086075 | -0.006308 | 0.039037 | -0.032444 | -0.007747 | 0.001233 | 0.001595 | -0.033968 | 0.086788 | -0.005744 | -0.069799 | -0.010725 | -0.093445 | 0.016556 | -0.043560 | -0.005079 | -0.005527 | 0.011613 | 0.016920 | 0.004927 | -0.025966 | 0.008229 | -0.034817 | -0.029940 | 0.029342 | -0.031771 | 0.036009 | -0.002412 | -0.000416 | 0.003624 | 0.008208 | -0.014555 | 0.034539 | 0.025032 | -0.040286 | 0.035464 | 0.028907 | 0.001159 | 0.010009 | 0.008411 | 0.028956 | 0.007719 | -0.068453 | 0.008113 | -0.019764 | -0.017743 | 0.018201 | 0.035645 | 0.040467 | -0.033520 | -0.043727 | 0.064253 | -0.008686 |
| ANC11 | -0.236754 | -0.232363 | -0.173163 | -0.218821 | -0.092483 | -0.266002 | -0.183397 | 0.145764 | -0.193055 | 0.213792 | -0.105452 | -0.110112 | 0.133055 | -0.139708 | 0.020109 | -0.075477 | -0.010590 | 0.016015 | 0.048187 | 0.047105 | 0.085590 | 0.017480 | -0.023924 | 0.100101 | -0.008601 | 0.255678 | 0.001262 | -0.098442 | -0.087083 | 0.068458 | 0.045531 | -0.027108 | 0.107149 | -0.016233 | 0.091943 | -0.116176 | 0.035810 | -0.186673 | 0.169415 | 0.050754 | -0.024278 | 0.034110 | -0.088622 | 0.041817 | -0.051209 | -0.096153 | 0.071898 | -0.097710 | 0.129037 | -0.156034 | 0.040082 | 0.241137 | -0.051574 | 0.004251 | -0.018876 | -0.147482 | -0.050747 | 0.032498 | -0.086323 | 0.110727 | -0.031653 | 0.095144 | 0.076325 | -0.055451 | -0.056704 | 0.134372 | -0.069522 | -0.053713 | 0.038545 | 0.044859 | -0.002918 | 0.131489 | 0.069254 | 0.010991 | -0.038517 | -0.058989 |
| ANC12 | -0.416669 | -0.737201 | 0.318179 | -0.167462 | -0.068587 | -0.107530 | -0.043139 | -0.067640 | 0.105290 | -0.068818 | -0.001546 | 0.029665 | -0.055488 | 0.095267 | 0.000746 | -0.005510 | 0.021254 | 0.014567 | 0.051860 | 0.076998 | 0.003802 | -0.066556 | 0.125421 | 0.019640 | 0.061282 | -0.012244 | 0.030334 | -0.024821 | 0.007597 | 0.060777 | 0.012893 | 0.060931 | -0.006886 | 0.010454 | -0.026718 | 0.017940 | 0.012953 | 0.045359 | -0.031146 | -0.036549 | -0.035958 | -0.017576 | 0.046186 | 0.010741 | -0.030804 | 0.011338 | -0.029972 | -0.002714 | -0.009963 | -0.031396 | -0.032612 | 0.007946 | -0.046543 | -0.039350 | -0.003932 | -0.052078 | 0.013722 | 0.036365 | -0.036719 | 0.039716 | 0.004409 | -0.032033 | -0.014046 | 0.004781 | 0.013845 | 0.027750 | -0.004058 | -0.021530 | -0.003144 | 0.032400 | -0.015296 | -0.020175 | 0.016749 | -0.063010 | -0.004562 | 0.023870 |
| ANC13 | -0.504687 | -0.264880 | 0.508369 | 0.310248 | -0.122267 | 0.016680 | 0.078849 | -0.123428 | -0.089864 | 0.002908 | -0.066560 | 0.071715 | 0.033203 | -0.111839 | 0.015590 | 0.026532 | 0.061760 | -0.006791 | -0.036854 | -0.113568 | -0.022586 | 0.105582 | 0.004242 | 0.090404 | 0.003092 | -0.015236 | 0.080983 | -0.088880 | 0.090855 | -0.025913 | -0.026851 | -0.080135 | -0.024680 | -0.000484 | 0.010294 | -0.033532 | 0.065210 | -0.065865 | -0.002534 | -0.060744 | 0.024321 | 0.009072 | -0.049079 | 0.032996 | 0.037491 | 0.020183 | 0.012801 | 0.110018 | -0.118716 | -0.036081 | -0.053192 | -0.044322 | 0.040393 | -0.031793 | 0.043818 | 0.041667 | -0.027857 | -0.088240 | 0.104347 | 0.042468 | -0.010132 | -0.071442 | 0.087312 | 0.016814 | -0.115288 | 0.074295 | 0.000537 | -0.043472 | -0.001772 | 0.017449 | 0.094793 | 0.161601 | 0.026062 | -0.020214 | 0.101914 | -0.004296 |
| ANC14 | -0.299467 | -0.188824 | 0.523885 | 0.210417 | 0.022357 | 0.143334 | -0.233283 | 0.088831 | -0.187568 | 0.057284 | -0.120129 | -0.107610 | -0.141688 | -0.019720 | -0.020492 | -0.121016 | -0.245535 | 0.011502 | 0.113584 | 0.030937 | -0.040115 | 0.098303 | 0.003290 | -0.110934 | -0.051716 | -0.124886 | -0.062544 | 0.026169 | -0.054121 | -0.003435 | 0.146155 | -0.032358 | -0.041685 | 0.046918 | -0.015167 | -0.123392 | -0.076058 | 0.072500 | -0.039029 | -0.035799 | 0.010988 | 0.032881 | -0.115017 | -0.076807 | 0.078274 | -0.048526 | 0.055725 | 0.073958 | -0.008329 | 0.004270 | -0.017202 | 0.035506 | 0.033859 | 0.017275 | 0.073561 | -0.066145 | 0.075921 | 0.015819 | 0.011551 | 0.042366 | -0.035574 | -0.019262 | 0.004545 | 0.044380 | 0.072012 | -0.026134 | -0.002973 | -0.135129 | 0.095459 | 0.051092 | -0.060454 | -0.065976 | 0.013293 | 0.169918 | 0.051166 | -0.090816 |
| ANC15 | -0.285677 | -0.484186 | 0.279530 | -0.083596 | 0.066897 | -0.046827 | -0.052614 | 0.153454 | 0.136603 | -0.048967 | -0.043587 | 0.060314 | -0.100271 | 0.049912 | -0.085482 | 0.072322 | -0.085115 | -0.029494 | -0.037395 | 0.145330 | 0.043119 | -0.064315 | 0.081783 | 0.129413 | 0.028182 | -0.008131 | -0.031355 | -0.041211 | 0.007713 | 0.053546 | -0.019467 | 0.070298 | 0.013085 | -0.066382 | -0.036202 | -0.108920 | -0.013310 | -0.037488 | 0.016473 | -0.040463 | -0.036879 | -0.004292 | 0.086460 | -0.091793 | -0.010460 | -0.047500 | -0.076901 | 0.302459 | -0.196420 | 0.043693 | -0.049138 | 0.261308 | -0.003565 | 0.167257 | -0.166237 | 0.247244 | 0.061297 | 0.109611 | -0.057412 | -0.108857 | -0.057603 | 0.049709 | -0.016776 | -0.057030 | -0.073146 | 0.074737 | 0.022702 | 0.019413 | 0.040794 | -0.027514 | -0.028861 | -0.043496 | 0.029414 | 0.027401 | -0.075115 | 0.010530 |
| POBC1 | -0.164407 | -0.603704 | -0.510744 | -0.364244 | 0.011695 | -0.363679 | -0.197010 | 0.086237 | -0.068481 | -0.023616 | 0.108701 | 0.018833 | -0.034837 | 0.053619 | -0.011601 | 0.008241 | 0.056264 | -0.037820 | -0.025715 | -0.012075 | 0.011767 | 0.006142 | 0.013626 | 0.022399 | 0.003122 | -0.035609 | -0.038381 | 0.024971 | 0.007457 | 0.024721 | -0.024117 | -0.012795 | 0.013947 | 0.025480 | 0.004331 | 0.003454 | 0.002838 | -0.009360 | -0.007316 | -0.011681 | 0.004015 | -0.000052 | 0.002057 | -0.002524 | -0.003330 | -0.001647 | -0.001867 | -0.002728 | -0.010631 | 0.002443 | -0.005961 | 0.005817 | -0.003322 | 0.008246 | 0.004935 | -0.001284 | 0.001931 | 0.000672 | -0.000066 | -0.003048 | 0.000339 | -0.009615 | 0.009151 | -0.008382 | -0.000216 | 0.001870 | -0.000285 | -0.010908 | -0.000485 | 0.006135 | -0.004649 | 0.002407 | -0.004817 | -0.004916 | -0.003501 | -0.005691 |
| POBC2 | 0.326437 | 0.780532 | 0.004196 | -0.044757 | 0.317294 | 0.310826 | -0.145072 | -0.068489 | 0.155235 | -0.008051 | 0.007172 | -0.089899 | 0.048869 | -0.021505 | 0.005753 | -0.000148 | 0.010805 | 0.051611 | -0.032702 | 0.059999 | 0.034983 | -0.035352 | -0.012321 | -0.028129 | -0.014078 | 0.034664 | 0.035111 | 0.023758 | -0.017334 | -0.020651 | -0.013940 | -0.005492 | -0.005983 | 0.012790 | -0.044401 | -0.010892 | 0.008377 | -0.006852 | 0.031890 | 0.019635 | 0.013753 | 0.002623 | -0.011329 | 0.006742 | 0.008665 | -0.010778 | 0.006204 | 0.011272 | 0.005153 | -0.001406 | -0.007055 | -0.022276 | 0.008464 | 0.000967 | -0.009629 | 0.004557 | 0.002656 | 0.005562 | -0.006862 | 0.011273 | 0.001895 | 0.010279 | -0.001329 | -0.002375 | 0.000367 | -0.007532 | -0.006163 | -0.004726 | -0.010070 | -0.001892 | -0.003395 | 0.011647 | -0.000820 | -0.005353 | -0.008845 | 0.007960 |
| LSC1 | -0.120405 | 0.433487 | 0.592577 | 0.466982 | 0.265839 | 0.221542 | 0.126273 | -0.208646 | 0.117892 | 0.082105 | -0.098922 | -0.043983 | 0.073222 | -0.036797 | 0.004529 | -0.002471 | -0.063096 | 0.011740 | 0.035947 | 0.005244 | -0.020853 | 0.011375 | -0.009933 | -0.001231 | 0.005298 | 0.017486 | 0.024408 | -0.022521 | -0.005084 | 0.001334 | 0.015319 | -0.002141 | 0.005005 | -0.010717 | 0.007329 | 0.007008 | 0.008121 | 0.007193 | -0.015958 | 0.004293 | -0.003620 | -0.000999 | -0.002938 | 0.003387 | 0.000049 | 0.003603 | 0.005505 | 0.009261 | 0.004670 | -0.002148 | 0.007466 | -0.003161 | -0.000590 | -0.003045 | 0.003763 | 0.005142 | -0.002254 | -0.001708 | -0.007943 | 0.001429 | 0.002466 | -0.002494 | 0.000090 | -0.008628 | 0.003397 | -0.001262 | -0.000723 | -0.003871 | 0.000814 | 0.000530 | -0.000896 | -0.012941 | 0.002382 | -0.003912 | -0.001840 | 0.001755 |
| LSC2 | 0.243069 | -0.109492 | -0.662153 | -0.358283 | 0.017870 | -0.393696 | -0.175402 | 0.059292 | -0.205410 | -0.198222 | 0.107158 | 0.113274 | -0.170897 | 0.007306 | 0.022032 | 0.030930 | 0.144814 | 0.024000 | -0.017319 | -0.050458 | 0.050531 | 0.000780 | -0.028063 | -0.022290 | -0.039258 | -0.013032 | 0.001592 | 0.035149 | -0.024493 | -0.017998 | 0.003426 | 0.009514 | -0.016538 | 0.020179 | -0.006874 | -0.019869 | 0.004153 | -0.007963 | 0.006486 | 0.005799 | -0.013169 | 0.000025 | -0.000107 | -0.001722 | -0.002749 | -0.007466 | -0.008828 | -0.006610 | -0.005532 | 0.003836 | -0.008286 | -0.001398 | 0.005091 | 0.005514 | -0.009905 | -0.009067 | -0.002584 | 0.002736 | 0.010816 | -0.001649 | -0.004335 | 0.003067 | -0.004276 | 0.012639 | -0.001871 | -0.003480 | -0.000842 | 0.007045 | -0.002561 | -0.004840 | 0.002455 | 0.010260 | -0.003562 | 0.006541 | -0.001121 | -0.000950 |
| LSC3 | -0.360872 | -0.484782 | -0.483361 | -0.362880 | 0.006647 | -0.219935 | -0.130383 | 0.107977 | -0.071376 | 0.228478 | 0.103224 | -0.123316 | 0.231268 | 0.063891 | -0.057117 | -0.066171 | -0.007127 | -0.102372 | -0.103737 | 0.002822 | -0.070366 | 0.031227 | -0.003649 | -0.003589 | 0.032057 | -0.038557 | -0.029849 | 0.041799 | 0.041020 | 0.000974 | -0.049908 | -0.006790 | -0.017890 | 0.027846 | -0.016160 | 0.018273 | 0.009705 | -0.007773 | -0.019992 | 0.000370 | 0.011128 | 0.006257 | -0.008376 | -0.005464 | -0.002494 | 0.006568 | -0.012128 | -0.009894 | -0.014329 | -0.003420 | 0.000337 | 0.003449 | -0.019794 | 0.009494 | 0.004407 | 0.013819 | 0.014912 | 0.006798 | -0.000486 | -0.004005 | 0.002333 | -0.003651 | -0.001360 | -0.000897 | 0.010309 | -0.000948 | 0.004734 | -0.005281 | 0.004325 | -0.000186 | 0.005092 | 0.011273 | -0.006537 | 0.009428 | 0.003005 | -0.008668 |
| LSC4 | -0.283634 | -0.755986 | 0.052922 | -0.221930 | 0.046875 | -0.111874 | -0.162246 | 0.090163 | 0.096454 | -0.033483 | 0.018880 | -0.051786 | -0.129683 | 0.110394 | -0.049321 | 0.066751 | -0.131269 | -0.023674 | -0.046600 | 0.194832 | 0.023330 | -0.126574 | 0.162759 | 0.123304 | 0.030825 | 0.000204 | -0.103762 | -0.045854 | 0.093402 | 0.080055 | -0.037630 | 0.004586 | 0.042572 | -0.039260 | 0.013020 | -0.008792 | -0.070940 | 0.000483 | 0.107660 | -0.030577 | 0.044489 | -0.009353 | 0.034075 | -0.009743 | 0.020116 | -0.003354 | 0.021931 | -0.014656 | 0.020735 | 0.009329 | -0.014065 | 0.016415 | 0.020603 | -0.012698 | 0.002636 | -0.024094 | 0.003185 | -0.010086 | 0.005496 | 0.004036 | 0.001415 | 0.008663 | 0.017241 | 0.005043 | -0.025590 | 0.018069 | -0.009360 | 0.001300 | -0.005139 | 0.009729 | -0.009308 | 0.024725 | 0.010074 | -0.018530 | 0.009896 | 0.000441 |
| VOC1 | -0.760241 | 0.429148 | 0.208713 | 0.302880 | 0.234827 | -0.133768 | -0.087644 | -0.073207 | -0.069452 | 0.032966 | -0.004439 | 0.034465 | 0.017601 | -0.017771 | 0.024436 | 0.015034 | 0.041225 | -0.023419 | 0.009489 | 0.033672 | 0.006589 | -0.010854 | 0.001428 | -0.009311 | 0.021924 | 0.013484 | 0.011442 | 0.028969 | 0.011944 | -0.011051 | -0.003264 | 0.003619 | 0.008973 | 0.007955 | 0.011399 | -0.015966 | -0.003763 | -0.000921 | -0.002931 | -0.007787 | -0.010031 | -0.003238 | -0.008527 | -0.000942 | 0.005897 | 0.002209 | -0.001840 | 0.000057 | 0.002263 | 0.005855 | -0.004134 | 0.002156 | 0.005456 | 0.001290 | 0.008471 | 0.000541 | 0.006266 | 0.003260 | -0.004604 | -0.003642 | 0.002004 | 0.002243 | 0.004045 | 0.001559 | 0.001347 | -0.003193 | -0.005532 | 0.006508 | -0.003370 | -0.006611 | -0.006269 | 0.002088 | -0.002021 | 0.002891 | 0.004811 | 0.003149 |
| VOC2 | -0.819743 | 0.560612 | 0.063436 | 0.051088 | -0.006045 | -0.001273 | -0.050617 | -0.012035 | -0.027035 | 0.030004 | 0.001899 | 0.009757 | 0.009899 | -0.024059 | 0.009427 | 0.005395 | 0.011129 | -0.000163 | 0.020378 | 0.002677 | -0.002296 | 0.004202 | -0.009304 | -0.001516 | -0.000706 | 0.005093 | -0.001596 | 0.012714 | 0.001478 | 0.004485 | -0.008103 | -0.003815 | 0.006971 | 0.001977 | -0.002481 | -0.003979 | -0.001529 | 0.002939 | -0.001843 | -0.009980 | -0.001102 | -0.001910 | -0.003683 | -0.001623 | -0.002267 | 0.001123 | -0.000633 | 0.001048 | 0.000213 | 0.006248 | 0.000883 | 0.001404 | 0.000319 | -0.002044 | -0.001225 | 0.000136 | -0.000768 | 0.002908 | -0.001306 | 0.001837 | -0.000392 | 0.002064 | 0.001442 | -0.001330 | -0.000296 | 0.000687 | 0.002438 | -0.003392 | -0.006683 | 0.002845 | -0.005191 | 0.000576 | 0.001261 | -0.000099 | 0.002712 | 0.002863 |
| VOC3 | -0.722539 | 0.654453 | 0.056145 | -0.098397 | -0.057453 | 0.012263 | -0.103240 | -0.039083 | -0.010568 | 0.086891 | 0.026420 | 0.031314 | 0.017057 | -0.046524 | 0.004796 | 0.006200 | -0.005054 | 0.032965 | 0.038413 | -0.013067 | -0.002140 | 0.016499 | -0.009570 | 0.006047 | -0.006859 | 0.007510 | -0.015814 | 0.001131 | -0.010361 | 0.005116 | -0.011316 | -0.010356 | -0.000562 | -0.006781 | -0.010733 | 0.002700 | -0.003860 | -0.002523 | -0.001194 | -0.019915 | 0.003062 | -0.007293 | -0.008187 | -0.003104 | -0.009763 | 0.006250 | -0.008982 | 0.001404 | -0.007695 | 0.011759 | 0.006750 | 0.005110 | -0.004632 | -0.007854 | 0.002149 | 0.001086 | -0.003832 | 0.007849 | 0.003623 | 0.006985 | -0.002248 | 0.003097 | 0.003918 | -0.000711 | -0.003043 | 0.004830 | 0.006283 | -0.008063 | -0.012857 | 0.009727 | -0.008674 | -0.000943 | 0.005825 | 0.003904 | 0.003446 | 0.003738 |
| HC1 | 0.028150 | 0.537311 | 0.541994 | -0.458370 | 0.351653 | 0.136945 | -0.059787 | 0.125153 | 0.076378 | 0.124989 | 0.008634 | 0.055368 | -0.024286 | 0.025174 | 0.014793 | 0.029055 | 0.067730 | 0.010865 | 0.012645 | 0.046724 | -0.030043 | -0.017978 | 0.001143 | 0.008615 | -0.024795 | 0.005129 | 0.009915 | -0.010036 | -0.001475 | 0.009467 | -0.004288 | -0.004659 | -0.009761 | -0.004086 | -0.007847 | -0.016570 | -0.010630 | 0.019262 | -0.008346 | 0.004908 | -0.009973 | -0.006591 | -0.002849 | 0.008931 | 0.010456 | -0.011124 | 0.006649 | 0.000359 | 0.009252 | 0.008779 | 0.000981 | -0.005081 | 0.012224 | -0.011541 | -0.006639 | 0.002402 | -0.014190 | 0.008144 | 0.001187 | -0.000987 | 0.000811 | -0.004740 | -0.004487 | 0.005077 | -0.003895 | 0.002598 | -0.006794 | 0.003087 | -0.017898 | -0.002314 | -0.003743 | 0.013480 | 0.007067 | 0.003455 | 0.003136 | -0.001891 |
| HC2 | 0.580877 | -0.142137 | 0.134753 | -0.403126 | 0.519146 | 0.290753 | -0.248132 | 0.085339 | -0.042305 | 0.063076 | -0.126025 | 0.031809 | -0.024393 | 0.057945 | 0.038655 | 0.044491 | -0.001883 | -0.003614 | -0.003750 | -0.046252 | -0.018424 | 0.000344 | -0.005829 | 0.036293 | -0.007914 | -0.009449 | 0.013551 | 0.025284 | 0.009707 | 0.005597 | -0.005935 | -0.001767 | -0.012158 | 0.002512 | 0.014074 | -0.005211 | 0.008088 | 0.001086 | -0.009453 | 0.004586 | -0.008074 | 0.002183 | -0.000556 | 0.000999 | 0.003095 | 0.006156 | -0.007821 | -0.007979 | -0.007839 | -0.008972 | -0.003726 | -0.002380 | 0.001883 | -0.000588 | 0.001205 | -0.001253 | -0.001483 | 0.002262 | -0.001560 | -0.000915 | 0.000805 | -0.009310 | -0.001950 | -0.001955 | -0.000641 | 0.006310 | -0.003655 | 0.002419 | 0.005055 | -0.000720 | 0.000991 | -0.011784 | 0.002754 | -0.000040 | -0.004319 | -0.001152 |
| HC3 | -0.595969 | 0.125007 | -0.137863 | 0.358589 | -0.383478 | -0.282254 | 0.180403 | -0.083021 | 0.029386 | -0.128139 | -0.102858 | -0.218149 | 0.016593 | -0.004421 | -0.021601 | 0.063156 | 0.018999 | -0.131660 | -0.005589 | -0.011112 | 0.073438 | 0.005808 | -0.119213 | -0.051628 | -0.023322 | -0.034063 | -0.016997 | 0.074860 | -0.052048 | 0.146354 | -0.022441 | 0.040651 | -0.020132 | -0.089336 | -0.018182 | -0.036739 | 0.027619 | 0.018095 | 0.080066 | 0.046740 | 0.048659 | 0.026118 | 0.015171 | 0.016679 | 0.033715 | 0.029900 | -0.014540 | -0.015836 | -0.013719 | -0.020904 | -0.024247 | -0.030166 | 0.004062 | 0.008583 | 0.021559 | 0.027516 | 0.011028 | 0.000118 | -0.005353 | 0.058395 | -0.022084 | 0.005519 | -0.001720 | -0.015390 | -0.009864 | -0.001808 | -0.003357 | -0.014480 | -0.001269 | -0.013330 | -0.004010 | -0.025052 | 0.025961 | -0.003887 | -0.010441 | 0.022233 |
| HC4 | -0.657279 | 0.154389 | -0.162798 | 0.401148 | -0.375149 | -0.266409 | 0.191524 | -0.110709 | 0.040525 | -0.124353 | -0.050139 | -0.188418 | 0.013853 | 0.007533 | -0.027068 | 0.045918 | 0.033554 | -0.093310 | -0.005562 | -0.015343 | 0.048200 | -0.000576 | -0.063016 | -0.026157 | -0.002701 | -0.012300 | -0.015902 | 0.034788 | -0.029621 | 0.076603 | -0.004010 | 0.033373 | -0.022734 | -0.036471 | -0.012745 | -0.016293 | 0.017717 | 0.010938 | 0.046600 | 0.032477 | 0.023746 | 0.010279 | 0.009243 | 0.008399 | 0.015822 | 0.008557 | -0.005309 | -0.003214 | -0.005828 | -0.008224 | -0.006103 | -0.019377 | -0.000713 | 0.007124 | 0.004325 | 0.012378 | 0.008151 | -0.006760 | 0.007137 | 0.017828 | -0.009731 | -0.001177 | 0.003185 | 0.002687 | -0.003126 | 0.003635 | 0.000746 | -0.000997 | -0.002095 | -0.009421 | -0.000858 | -0.006454 | 0.007732 | 0.000188 | -0.003751 | -0.000382 |
| HC5 | -0.619904 | 0.174579 | -0.154415 | 0.447219 | -0.400875 | -0.289619 | 0.191473 | -0.148119 | 0.024204 | -0.113160 | -0.011177 | -0.158418 | 0.001330 | 0.001022 | -0.034613 | 0.010590 | 0.030137 | -0.070712 | -0.011075 | -0.007996 | 0.026258 | -0.013139 | -0.025757 | -0.021797 | 0.012267 | -0.003669 | -0.010935 | 0.014793 | -0.012448 | 0.042908 | 0.000323 | 0.032733 | -0.020933 | -0.008286 | -0.005575 | -0.012472 | 0.006179 | 0.003014 | 0.027790 | 0.025468 | 0.015064 | 0.002601 | 0.010565 | 0.002810 | 0.012157 | -0.002886 | 0.000328 | 0.000671 | -0.000428 | -0.000774 | -0.000937 | -0.010887 | -0.004070 | 0.001216 | -0.005231 | 0.004291 | 0.002554 | -0.006328 | 0.007277 | 0.005074 | -0.004434 | 0.000576 | 0.004567 | 0.006447 | 0.000065 | 0.001162 | 0.000497 | 0.004670 | -0.005022 | -0.005780 | -0.000640 | 0.002849 | 0.000537 | -0.000164 | -0.001753 | -0.005693 |
| HC6 | -0.631975 | 0.291584 | -0.047651 | 0.432792 | -0.379724 | -0.296629 | 0.171377 | -0.178744 | 0.015644 | -0.057524 | 0.097025 | -0.076414 | 0.002212 | -0.023729 | -0.045774 | -0.039881 | -0.019988 | -0.019921 | -0.003401 | 0.015775 | 0.016758 | -0.017988 | 0.011187 | -0.015225 | 0.029232 | 0.001850 | -0.019340 | -0.026519 | -0.007288 | -0.003367 | 0.016456 | 0.035966 | -0.004898 | 0.021421 | -0.006141 | -0.000031 | -0.001256 | -0.006246 | 0.000970 | 0.009628 | 0.006652 | -0.006752 | 0.001863 | -0.003148 | 0.001101 | -0.006087 | 0.007920 | 0.002559 | 0.006197 | 0.005023 | 0.004097 | 0.000735 | -0.000193 | 0.000144 | -0.005134 | -0.000564 | 0.001523 | -0.003197 | 0.008797 | -0.001710 | -0.000992 | 0.001911 | 0.004872 | 0.006350 | -0.001299 | -0.002260 | -0.001028 | 0.004082 | -0.009988 | 0.004954 | -0.001337 | 0.011462 | -0.002340 | -0.002488 | -0.001588 | -0.004553 |
| HC7 | -0.691819 | 0.293499 | 0.015858 | 0.390169 | -0.294734 | -0.301603 | 0.187308 | -0.163504 | 0.021487 | -0.018703 | 0.148484 | -0.007752 | 0.016731 | -0.040228 | -0.041534 | -0.050414 | -0.017201 | 0.005521 | -0.000099 | 0.049868 | 0.015940 | -0.016006 | 0.001816 | -0.027210 | 0.016013 | 0.012487 | -0.025062 | -0.041048 | 0.004114 | -0.017714 | 0.017395 | 0.020549 | 0.015387 | 0.018538 | -0.016247 | 0.012460 | -0.011712 | -0.004239 | -0.006159 | 0.001560 | 0.004290 | -0.005945 | 0.000092 | -0.003144 | -0.007772 | -0.006016 | 0.011621 | 0.005690 | 0.008768 | 0.009419 | 0.007779 | 0.005566 | 0.003381 | -0.000454 | -0.003537 | -0.000230 | 0.002202 | -0.002009 | 0.006162 | 0.001304 | 0.001142 | 0.003773 | 0.001321 | 0.000843 | -0.003437 | -0.004167 | 0.000246 | -0.000077 | -0.012237 | 0.006579 | -0.001674 | 0.016927 | -0.000148 | -0.001799 | -0.000550 | -0.000432 |
| HC8 | 0.662636 | -0.227143 | 0.026102 | -0.348895 | 0.462018 | 0.259142 | -0.218312 | 0.101030 | -0.029625 | 0.022871 | -0.155984 | 0.001448 | -0.016725 | 0.042759 | 0.043087 | 0.059679 | 0.019673 | -0.007220 | -0.004199 | -0.048739 | -0.016652 | 0.015257 | -0.002194 | 0.030885 | -0.019795 | -0.012485 | 0.025998 | 0.043208 | -0.001561 | 0.020230 | -0.018028 | -0.018369 | -0.017700 | -0.016637 | 0.017538 | -0.014016 | 0.012969 | 0.004481 | 0.007446 | 0.000542 | -0.004887 | 0.006330 | -0.000311 | 0.003169 | 0.008837 | 0.005821 | -0.012334 | -0.006146 | -0.008823 | -0.009168 | -0.007962 | -0.006367 | -0.002733 | 0.000937 | 0.003505 | 0.000323 | -0.001882 | 0.002240 | -0.006972 | -0.001074 | -0.000984 | -0.004161 | -0.001442 | -0.000805 | 0.004107 | 0.004031 | -0.000650 | -0.000246 | 0.012415 | -0.007055 | 0.001897 | -0.017024 | -0.000133 | 0.001831 | 0.000146 | 0.000125 |
| HC9 | -0.330618 | -0.824573 | 0.178358 | 0.102465 | -0.070049 | -0.197438 | 0.052090 | -0.008470 | 0.130577 | -0.028608 | 0.124817 | -0.020880 | -0.027429 | 0.038409 | -0.015520 | -0.089118 | 0.016644 | 0.018112 | 0.043666 | 0.096227 | 0.044733 | -0.041504 | 0.012429 | 0.024925 | 0.045629 | 0.020904 | 0.045508 | -0.002925 | 0.036506 | -0.021702 | 0.101486 | 0.098257 | 0.007477 | 0.087514 | -0.012092 | 0.023755 | 0.032698 | 0.017688 | -0.041869 | 0.038796 | 0.020487 | 0.019356 | -0.045561 | 0.018256 | 0.019035 | -0.020816 | -0.043976 | -0.014065 | 0.003022 | 0.015854 | -0.014801 | -0.016384 | -0.031059 | -0.021914 | -0.000849 | 0.018395 | -0.001498 | 0.010916 | 0.021758 | -0.003035 | -0.031986 | -0.020327 | -0.003627 | 0.030572 | -0.019909 | 0.032724 | 0.001442 | -0.007498 | -0.012869 | 0.023849 | -0.003925 | -0.011768 | 0.008206 | 0.001277 | -0.012183 | 0.002555 |
| HC10 | -0.117531 | -0.876578 | -0.163374 | 0.203287 | -0.072320 | -0.166167 | 0.007962 | -0.068631 | 0.048862 | 0.003854 | 0.151664 | 0.031943 | -0.021001 | 0.019164 | -0.022735 | -0.122947 | 0.029031 | 0.023733 | 0.029339 | 0.059751 | 0.021394 | -0.022107 | 0.007751 | 0.028265 | 0.015498 | 0.034037 | 0.054168 | 0.011125 | 0.035123 | -0.022078 | 0.080440 | 0.059521 | 0.034980 | 0.083621 | -0.008414 | 0.023790 | 0.019048 | 0.014742 | -0.048362 | 0.040099 | 0.018773 | 0.014167 | -0.055360 | 0.023562 | 0.027700 | -0.030579 | -0.036029 | -0.011387 | 0.006735 | 0.021268 | -0.003691 | -0.009854 | -0.025691 | -0.014054 | 0.000991 | 0.030847 | -0.012877 | 0.012630 | 0.022310 | -0.023520 | -0.045738 | -0.015680 | 0.004410 | 0.018729 | -0.021684 | 0.030156 | -0.004722 | 0.007201 | -0.023020 | 0.022812 | -0.002402 | -0.008505 | 0.017956 | 0.020998 | -0.002521 | -0.000155 |
| HC11 | -0.466259 | -0.326611 | -0.275503 | -0.346734 | 0.545105 | 0.195379 | -0.019991 | 0.193675 | -0.061789 | -0.133067 | -0.111665 | -0.028133 | 0.053966 | -0.060343 | 0.028995 | 0.026655 | -0.062134 | 0.061308 | -0.029928 | 0.083716 | 0.020597 | -0.082588 | -0.101200 | -0.072818 | 0.011636 | -0.060804 | -0.000077 | 0.021211 | -0.010540 | -0.038759 | -0.034791 | 0.066694 | 0.014723 | 0.003261 | 0.000639 | -0.031873 | 0.035298 | -0.014044 | 0.002160 | -0.014566 | 0.012414 | -0.006018 | 0.020015 | -0.001984 | -0.001526 | 0.018141 | 0.005961 | -0.010055 | 0.008961 | -0.010477 | 0.005523 | -0.012024 | 0.011946 | 0.014643 | 0.017864 | 0.013638 | -0.004199 | -0.006513 | 0.012478 | 0.016557 | -0.011879 | 0.002926 | 0.004420 | -0.010864 | -0.021905 | 0.001536 | -0.004163 | -0.023387 | 0.000846 | 0.017497 | 0.011804 | -0.014229 | 0.022430 | 0.007561 | 0.003784 | -0.011522 |
| HC12 | 0.416656 | 0.738816 | 0.249487 | 0.036616 | -0.299434 | -0.065119 | -0.156566 | -0.207375 | 0.081938 | 0.121723 | -0.000234 | -0.063308 | -0.057576 | 0.022453 | -0.005928 | 0.038128 | 0.049014 | 0.017963 | -0.009901 | 0.010198 | 0.000932 | -0.028661 | -0.012942 | 0.006437 | 0.010598 | 0.012371 | -0.002530 | 0.024274 | -0.017063 | -0.032835 | -0.032444 | 0.012844 | -0.007155 | 0.006962 | -0.004846 | 0.008128 | 0.002264 | 0.008593 | 0.005046 | -0.009170 | -0.007254 | 0.003038 | -0.000539 | -0.005437 | -0.017740 | 0.008759 | -0.008557 | -0.010232 | -0.001521 | -0.007188 | 0.008906 | -0.000893 | 0.013333 | -0.001222 | -0.003559 | 0.002800 | -0.006469 | 0.000679 | -0.003209 | -0.017439 | -0.001554 | 0.008632 | -0.023383 | -0.005226 | 0.007536 | 0.006327 | 0.001533 | -0.002197 | -0.003416 | -0.002783 | -0.004107 | 0.002578 | 0.009553 | 0.011908 | 0.007847 | -0.016099 |
| HC13 | 0.102199 | -0.328572 | 0.134030 | 0.592905 | -0.256725 | -0.406507 | 0.272837 | -0.188827 | 0.007586 | -0.021349 | 0.178523 | 0.109759 | -0.038107 | 0.050881 | -0.043631 | -0.043328 | 0.102310 | -0.091101 | 0.027902 | -0.109862 | -0.052209 | 0.072237 | 0.106621 | 0.085557 | 0.026901 | 0.089024 | -0.013004 | -0.036243 | 0.004725 | 0.064783 | 0.028505 | -0.090300 | -0.012547 | -0.015650 | 0.004846 | 0.063737 | -0.070013 | 0.003583 | -0.021601 | 0.042258 | -0.029698 | 0.004738 | -0.015096 | 0.001369 | -0.013663 | -0.027829 | 0.005184 | 0.019529 | -0.000799 | 0.014322 | -0.003754 | 0.020555 | -0.017667 | -0.005758 | -0.023676 | -0.021699 | 0.011985 | 0.008508 | -0.017802 | -0.020311 | 0.020712 | -0.011038 | 0.000419 | 0.007807 | 0.036687 | -0.003667 | 0.012145 | 0.029434 | -0.004257 | -0.014494 | -0.011614 | 0.022573 | -0.026624 | 0.001034 | -0.004268 | -0.000754 |
| HC14 | 0.362414 | 0.616019 | 0.323260 | 0.106491 | -0.054151 | 0.254419 | -0.228374 | -0.084724 | 0.147902 | 0.165007 | 0.025170 | -0.019058 | -0.033716 | 0.119607 | -0.018472 | 0.018843 | 0.002954 | -0.084980 | 0.114432 | -0.045293 | 0.051411 | 0.171441 | 0.099989 | 0.068057 | -0.103007 | -0.045318 | -0.021301 | -0.027339 | 0.073083 | 0.031510 | 0.059522 | -0.076276 | -0.077059 | 0.013571 | -0.042580 | -0.012135 | -0.046851 | 0.020016 | 0.015847 | 0.036482 | 0.035795 | 0.004696 | -0.040082 | 0.021480 | 0.031856 | 0.005252 | -0.050184 | -0.018683 | -0.034602 | -0.009206 | -0.036266 | -0.021457 | -0.007162 | -0.018683 | 0.026116 | 0.010195 | -0.027978 | 0.011597 | -0.026012 | -0.001070 | 0.003263 | -0.012399 | -0.019328 | 0.039879 | -0.043378 | 0.014715 | -0.042320 | 0.060237 | 0.043959 | -0.073333 | 0.014579 | 0.008975 | -0.038223 | -0.042608 | -0.059585 | 0.042762 |
| HC15 | -0.259253 | 0.008410 | -0.110353 | -0.103336 | -0.195182 | -0.126232 | -0.072417 | -0.013088 | -0.143511 | 0.224743 | -0.000524 | -0.054332 | 0.020446 | -0.057424 | -0.015927 | -0.073198 | 0.037920 | -0.036889 | -0.050452 | -0.111001 | 0.048343 | 0.014577 | 0.087837 | -0.007986 | -0.165817 | 0.136412 | 0.117216 | -0.029314 | -0.150667 | -0.022725 | 0.085794 | 0.137306 | 0.141429 | -0.056415 | -0.010443 | -0.094468 | 0.053956 | 0.013353 | 0.060448 | -0.171455 | 0.002078 | -0.053702 | 0.253284 | -0.138674 | 0.115845 | -0.043279 | 0.050042 | -0.043825 | -0.131955 | 0.218603 | 0.369292 | -0.086169 | -0.195734 | -0.194801 | 0.108087 | 0.018954 | 0.128880 | 0.028625 | 0.094416 | -0.061753 | 0.252230 | 0.037497 | -0.052456 | -0.023002 | -0.111679 | 0.049768 | -0.053396 | -0.037334 | 0.104494 | -0.016942 | 0.021877 | 0.035338 | -0.050462 | 0.013852 | -0.072030 | -0.034765 |
| HC16 | 0.386062 | 0.701724 | 0.290717 | 0.079711 | -0.314088 | -0.035675 | -0.211624 | -0.191505 | -0.014217 | 0.173040 | -0.043435 | -0.038548 | -0.057412 | -0.034293 | 0.015962 | -0.011501 | -0.063623 | 0.042219 | -0.017497 | -0.005666 | 0.004566 | 0.057680 | 0.043396 | 0.026555 | -0.005323 | -0.030935 | 0.005880 | 0.004836 | 0.032877 | 0.031704 | 0.031789 | -0.012967 | 0.025234 | 0.020843 | 0.019467 | -0.015665 | 0.056407 | 0.012231 | 0.025220 | -0.046654 | 0.005880 | 0.004177 | -0.014714 | 0.002857 | 0.029912 | -0.018673 | 0.013869 | 0.014290 | -0.001451 | 0.019577 | 0.003524 | 0.016427 | -0.020742 | -0.021653 | -0.025086 | -0.012897 | 0.012631 | 0.004272 | 0.014327 | 0.009854 | -0.004390 | 0.008639 | 0.024541 | 0.002349 | 0.012141 | -0.014817 | 0.009234 | -0.019072 | -0.018337 | 0.021610 | -0.019876 | -0.007354 | -0.009550 | -0.013549 | 0.026501 | 0.031184 |
| HC17 | -0.220383 | -0.740298 | -0.217732 | -0.030537 | 0.472126 | -0.057458 | 0.199621 | 0.078874 | -0.149117 | -0.147246 | -0.018820 | 0.023163 | 0.082144 | -0.024965 | 0.015363 | -0.039783 | 0.011754 | 0.000469 | -0.037412 | -0.009969 | -0.023426 | -0.072483 | -0.048466 | -0.014839 | 0.027531 | -0.008089 | 0.005973 | -0.012768 | 0.017541 | 0.027471 | 0.040374 | 0.012208 | 0.006640 | -0.016335 | 0.013930 | 0.030520 | -0.032442 | 0.001596 | -0.009128 | -0.004267 | -0.009985 | 0.009683 | 0.002289 | -0.023258 | -0.002901 | 0.000407 | 0.035314 | 0.027731 | 0.006066 | 0.012617 | -0.001138 | -0.012445 | 0.027363 | 0.005813 | -0.013213 | -0.000809 | -0.002987 | -0.001061 | -0.010637 | 0.006191 | 0.036539 | -0.010465 | 0.009016 | -0.015669 | 0.002375 | 0.000121 | 0.001743 | 0.000366 | -0.022717 | -0.000548 | -0.009735 | 0.027181 | -0.006306 | -0.011769 | -0.010751 | -0.004897 |
| HC18 | 0.141367 | 0.813917 | 0.254630 | 0.106801 | -0.287447 | -0.003516 | -0.221418 | -0.154136 | 0.146501 | 0.147269 | 0.020358 | -0.029993 | -0.080997 | 0.028069 | -0.018133 | 0.048516 | -0.007495 | -0.003632 | 0.036707 | 0.015189 | 0.023808 | 0.072488 | 0.047138 | 0.014158 | -0.029975 | 0.009436 | -0.008687 | 0.014035 | -0.020098 | -0.026815 | -0.046207 | -0.011493 | -0.008703 | 0.018799 | -0.016236 | -0.034516 | 0.031862 | -0.003289 | 0.008376 | 0.008952 | 0.008485 | -0.011328 | -0.000539 | 0.023275 | 0.002753 | 0.000300 | -0.037828 | -0.030180 | -0.005769 | -0.013175 | 0.001260 | 0.012649 | -0.027937 | -0.004135 | 0.014746 | 0.000103 | 0.003323 | 0.002129 | 0.010696 | -0.007023 | -0.038156 | 0.010217 | -0.011462 | 0.016569 | -0.002265 | 0.000132 | -0.002861 | 0.000343 | 0.023488 | -0.000099 | 0.011140 | -0.027956 | 0.007917 | 0.013404 | 0.010582 | 0.002844 |
| HC19 | -0.176543 | -0.802240 | -0.235055 | -0.067363 | 0.436000 | 0.032903 | 0.115529 | 0.116487 | -0.123396 | -0.127890 | -0.016014 | 0.007110 | 0.041606 | 0.004766 | 0.005850 | -0.053690 | -0.015235 | -0.009509 | 0.002915 | 0.026992 | -0.003553 | -0.048029 | -0.041017 | -0.012598 | 0.008159 | -0.016352 | 0.004818 | 0.006348 | 0.016200 | 0.002032 | 0.021346 | 0.012150 | -0.000638 | -0.005373 | 0.003755 | 0.007768 | -0.013661 | -0.007600 | -0.016756 | 0.003074 | -0.002757 | 0.007190 | 0.000917 | -0.008214 | 0.002394 | 0.000356 | 0.015979 | 0.004816 | 0.001884 | -0.002226 | 0.000913 | -0.006870 | 0.012427 | 0.003601 | -0.003444 | 0.000953 | -0.002606 | 0.000566 | -0.002024 | 0.005532 | 0.009164 | -0.005668 | 0.006744 | -0.011442 | -0.005398 | -0.001238 | -0.006436 | 0.007805 | -0.002496 | -0.003567 | 0.004500 | 0.007622 | -0.003776 | -0.003725 | -0.004972 | 0.000531 |
| HC20 | -0.353632 | 0.200302 | 0.156537 | 0.308005 | 0.750258 | -0.244672 | -0.087775 | -0.282725 | -0.031838 | 0.005041 | -0.004786 | -0.017697 | 0.019812 | 0.003885 | -0.003422 | 0.027394 | 0.014139 | -0.008539 | -0.013099 | 0.004172 | -0.006807 | 0.000861 | -0.014589 | 0.000292 | -0.001433 | 0.004431 | 0.000699 | 0.006544 | -0.007474 | 0.007384 | -0.011909 | 0.005983 | 0.001981 | 0.006352 | -0.000562 | -0.012114 | 0.005351 | -0.004238 | -0.011712 | 0.011295 | -0.013720 | -0.002764 | -0.000659 | -0.003002 | -0.000200 | -0.002254 | -0.000529 | -0.001208 | -0.003279 | 0.005506 | -0.000390 | 0.001430 | -0.000389 | 0.006128 | 0.002551 | -0.005970 | 0.002456 | 0.005719 | -0.000680 | 0.001955 | -0.001869 | -0.001762 | -0.001479 | -0.000053 | -0.001107 | -0.000789 | -0.002927 | -0.000626 | 0.000793 | -0.002689 | 0.002564 | 0.000717 | 0.001913 | -0.002585 | -0.001668 | -0.001229 |
| HC21 | -0.742859 | -0.003485 | 0.220360 | 0.273861 | 0.529663 | -0.145621 | -0.083592 | -0.079455 | -0.027610 | 0.054277 | 0.021017 | -0.028726 | -0.019318 | 0.016999 | -0.000577 | 0.009838 | 0.000608 | -0.008125 | 0.019787 | 0.004536 | -0.008117 | 0.014821 | -0.000289 | -0.005094 | 0.010925 | 0.004011 | 0.009821 | 0.012742 | -0.012116 | 0.011425 | -0.013201 | -0.002730 | -0.000438 | 0.005373 | -0.000116 | -0.014629 | 0.004687 | -0.001141 | -0.009052 | 0.010679 | -0.000848 | -0.004721 | -0.003157 | 0.004192 | 0.001334 | -0.004724 | -0.000845 | 0.000296 | -0.002224 | 0.003920 | 0.003756 | 0.004999 | -0.001194 | 0.005570 | 0.010925 | -0.001441 | 0.003572 | 0.002420 | 0.003219 | 0.003798 | -0.003085 | 0.002334 | 0.006334 | 0.000897 | -0.003886 | -0.002446 | -0.004151 | 0.002696 | -0.002003 | -0.000640 | -0.001075 | 0.000478 | 0.002907 | -0.005466 | -0.004345 | 0.000268 |
| MHUC1 | -0.897014 | -0.348651 | 0.040062 | -0.135160 | -0.075551 | -0.079133 | -0.061200 | -0.146834 | 0.023359 | -0.027670 | -0.034455 | -0.043113 | 0.034077 | 0.017106 | 0.042092 | 0.011426 | -0.004160 | 0.023422 | 0.021243 | -0.004782 | 0.030684 | -0.014364 | 0.003727 | -0.001265 | 0.016706 | 0.000172 | -0.003631 | 0.014249 | -0.006524 | 0.006188 | -0.008923 | 0.001370 | -0.012656 | 0.003179 | 0.004259 | 0.004170 | -0.001148 | 0.003447 | 0.013947 | -0.001449 | -0.000813 | -0.000200 | -0.005657 | -0.000078 | 0.000510 | -0.000806 | 0.003668 | -0.000032 | -0.004169 | 0.002036 | 0.003336 | -0.005714 | 0.006218 | 0.000454 | 0.001063 | 0.006275 | -0.001357 | 0.005681 | -0.006755 | 0.007912 | 0.001701 | -0.000254 | -0.005857 | 0.002868 | 0.001418 | 0.003694 | 0.001971 | 0.004968 | 0.000947 | -0.002848 | 0.000391 | -0.001386 | -0.002063 | 0.001482 | 0.002259 | 0.005565 |
| MHUC2 | -0.907671 | -0.145130 | 0.194468 | -0.039934 | 0.094893 | 0.043162 | 0.015344 | -0.150930 | 0.086755 | -0.095790 | 0.042367 | -0.001913 | -0.066071 | 0.078216 | 0.045720 | 0.009989 | -0.063009 | 0.009602 | 0.005577 | 0.026915 | 0.036881 | -0.004280 | 0.000306 | -0.012016 | -0.018807 | 0.026183 | 0.025757 | 0.020175 | 0.014828 | -0.017674 | -0.015887 | 0.012894 | -0.009349 | 0.013575 | -0.001752 | -0.016523 | -0.006327 | -0.029632 | -0.011505 | -0.019835 | 0.019473 | 0.017107 | -0.018406 | -0.014037 | 0.003198 | 0.009544 | -0.025715 | -0.028023 | -0.013536 | -0.003302 | -0.000494 | -0.004676 | 0.003524 | 0.008595 | 0.009595 | 0.021003 | 0.003622 | -0.002327 | -0.028461 | 0.004861 | 0.013591 | -0.003038 | 0.024197 | -0.010844 | 0.020170 | 0.000202 | 0.009861 | -0.012451 | -0.003249 | -0.010276 | 0.007961 | 0.019757 | -0.044888 | 0.010290 | -0.015432 | -0.001251 |
| AC1 | -0.240460 | 0.405926 | 0.728596 | -0.230851 | 0.115177 | -0.087403 | 0.034474 | -0.063998 | 0.028355 | 0.139022 | 0.021852 | 0.221124 | -0.014957 | 0.008724 | 0.037132 | -0.032750 | 0.007929 | 0.003029 | -0.074880 | 0.055160 | 0.028301 | 0.009578 | -0.108811 | -0.069657 | -0.091230 | 0.045970 | -0.074814 | 0.019105 | 0.047847 | 0.012084 | -0.020445 | 0.002072 | 0.092053 | -0.001594 | -0.026514 | 0.041383 | -0.026233 | 0.044653 | 0.007929 | 0.028682 | 0.041446 | 0.049030 | 0.008049 | -0.005349 | -0.036499 | -0.010854 | -0.014887 | 0.010052 | -0.036221 | -0.020549 | -0.000671 | 0.022820 | 0.000751 | -0.026443 | -0.005203 | -0.008285 | 0.023026 | -0.020632 | 0.025646 | 0.026757 | 0.001921 | -0.015587 | -0.004584 | -0.001690 | 0.007889 | 0.007781 | -0.008836 | 0.013928 | 0.019781 | 0.018932 | -0.013896 | 0.005842 | -0.004610 | -0.010607 | -0.007926 | -0.002872 |
| AC2 | 0.176910 | 0.071614 | 0.905985 | -0.166770 | 0.107689 | -0.189005 | 0.057495 | 0.024622 | -0.001777 | 0.073052 | -0.043014 | 0.102756 | -0.035063 | 0.029055 | 0.044204 | -0.014775 | 0.007609 | -0.066012 | -0.057078 | 0.051610 | 0.014395 | 0.025069 | -0.056225 | -0.051111 | -0.019405 | 0.015701 | 0.008605 | 0.016085 | 0.016210 | 0.011871 | -0.008454 | -0.013114 | 0.022391 | -0.007370 | -0.000617 | -0.000130 | -0.000581 | -0.000448 | 0.013986 | -0.006797 | -0.018921 | 0.002642 | 0.010175 | 0.012082 | 0.023594 | -0.016930 | -0.006629 | -0.000748 | 0.012128 | -0.001065 | -0.019315 | -0.023173 | -0.006915 | 0.002986 | -0.004369 | 0.016119 | -0.016932 | 0.010948 | -0.019318 | -0.010895 | 0.001023 | -0.008829 | -0.004391 | -0.006814 | 0.002731 | 0.011763 | 0.018159 | -0.018203 | -0.017968 | -0.024191 | 0.012144 | -0.000089 | 0.001706 | 0.006520 | 0.001713 | 0.001246 |
dic['print_df_pca4'] #GIVING HISTORY
| PC0 | PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | PC11 | PC12 | PC13 | PC14 | PC15 | PC16 | PC17 | PC18 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| N_RDATE_3 | 0.096254 | -0.024900 | 0.008905 | -0.004910 | 0.346758 | 0.725041 | 0.030302 | -0.285040 | -0.038494 | -0.287369 | -0.168640 | -0.049020 | 0.029026 | 0.369846 | 0.003910 | -0.007238 | 0.011742 | -0.031843 | 0.012091 |
| N_RDATE_4 | 0.108273 | -0.000310 | 0.030903 | -0.012224 | 0.206864 | 0.414575 | 0.033848 | -0.117810 | -0.061584 | -0.041259 | 0.036972 | -0.014137 | -0.133976 | -0.799428 | 0.221301 | -0.087126 | -0.009781 | 0.057536 | -0.071795 |
| N_RDATE_5 | 0.001434 | 0.273906 | -0.173219 | -0.358281 | 0.134913 | -0.198618 | -0.271754 | 0.065006 | 0.015133 | -0.151791 | 0.063125 | 0.166411 | 0.142764 | 0.577995 | -0.268728 | 0.115563 | 0.059910 | -0.175147 | 0.217761 |
| N_RDATE_6 | -0.014434 | -0.034430 | 0.422572 | 0.897342 | 0.099237 | -0.062647 | -0.001485 | -0.016059 | 0.002634 | -0.024586 | 0.001202 | -0.011024 | -0.005126 | 0.000068 | 0.002109 | -0.001309 | -0.000720 | 0.003620 | 0.001725 |
| N_RDATE_7 | -0.059842 | 0.256276 | 0.004902 | -0.056579 | 0.519688 | -0.105174 | 0.105941 | -0.446840 | 0.140114 | 0.481706 | 0.294286 | -0.034942 | 0.181412 | 0.018090 | -0.042656 | 0.096468 | 0.034240 | 0.051266 | 0.055117 |
| N_RDATE_8 | -0.240663 | -0.281022 | 0.269537 | -0.027105 | -0.455229 | 0.462029 | 0.120289 | 0.133279 | -0.209977 | 0.382115 | -0.044338 | -0.122825 | 0.084857 | 0.000692 | -0.024554 | 0.088702 | 0.018489 | 0.074948 | 0.045202 |
| N_RDATE_9 | -0.029249 | -0.084348 | -0.668300 | 0.313657 | 0.071131 | 0.164779 | -0.086777 | 0.245334 | 0.214011 | 0.035099 | 0.111777 | 0.028627 | -0.016178 | 0.038330 | -0.061907 | -0.421575 | -0.090847 | 0.105412 | -0.065072 |
| N_RDATE_10 | 0.202906 | 0.434678 | -0.043350 | 0.070504 | -0.368146 | 0.003390 | 0.348412 | -0.314504 | 0.217678 | -0.109305 | -0.128212 | 0.343686 | -0.257395 | 0.049310 | 0.211577 | 0.154759 | -0.113188 | 0.069577 | -0.096649 |
| N_RDATE_11 | 0.052865 | 0.245422 | 0.039732 | -0.055845 | 0.362531 | -0.087785 | 0.262918 | 0.397803 | -0.611108 | -0.242066 | 0.201033 | 0.136855 | -0.072879 | 0.060469 | 0.074252 | 0.081052 | -0.001812 | 0.021587 | -0.031478 |
| N_RDATE_12 | -0.006390 | -0.492824 | 0.257692 | -0.179098 | 0.314544 | -0.118881 | -0.470720 | 0.065077 | 0.222147 | -0.112351 | -0.256848 | 0.223918 | -0.152041 | -0.021417 | 0.093892 | 0.141711 | -0.026782 | 0.024413 | -0.060366 |
| N_RDATE_13 | 0.636232 | -0.038969 | -0.022852 | 0.019038 | -0.010401 | 0.039284 | -0.026732 | -0.020591 | -0.072897 | -0.068655 | -0.073924 | 0.124205 | 0.164113 | -0.155398 | -0.599705 | 0.198649 | -0.190100 | 0.163520 | 0.068528 |
| N_RDATE_14 | 0.323703 | -0.237892 | 0.090674 | -0.077636 | 0.007447 | -0.104533 | 0.380592 | 0.074150 | 0.374099 | -0.402266 | 0.152830 | -0.520533 | 0.005846 | -0.060505 | -0.012711 | 0.089565 | 0.006470 | -0.023653 | 0.102548 |
| N_RDATE_15 | 0.755112 | -0.095425 | 0.069990 | -0.020367 | 0.026013 | 0.040580 | 0.023391 | 0.162103 | 0.054268 | 0.190011 | -0.008878 | 0.111540 | 0.021125 | 0.044185 | 0.181776 | -0.070811 | 0.341980 | -0.055755 | 0.280432 |
| N_RDATE_16 | 0.385925 | 0.206042 | -0.079005 | 0.044547 | -0.226799 | -0.153673 | -0.369261 | -0.390782 | -0.321155 | -0.243311 | -0.098577 | -0.193755 | 0.221348 | -0.090465 | -0.000024 | -0.128119 | 0.173636 | -0.227323 | -0.057990 |
| N_RDATE_17 | 0.275910 | 0.292551 | 0.043134 | -0.024920 | 0.190116 | -0.026231 | 0.163982 | 0.144016 | 0.029394 | 0.268004 | -0.450249 | -0.219704 | -0.462094 | -0.017893 | -0.320829 | -0.100683 | 0.139943 | -0.192403 | -0.148823 |
| N_RDATE_18 | 0.396591 | -0.294094 | 0.162994 | -0.056822 | -0.045840 | 0.087139 | 0.254255 | 0.039135 | 0.172071 | -0.070589 | 0.271782 | 0.432834 | 0.188692 | -0.030672 | -0.184491 | -0.146594 | 0.134305 | -0.370809 | -0.220576 |
| N_RDATE_19 | 0.363484 | -0.137878 | -0.533320 | 0.252869 | -0.002143 | 0.048441 | -0.046609 | 0.050509 | -0.054717 | 0.041958 | -0.038407 | 0.004555 | -0.028463 | -0.054648 | 0.105114 | 0.581474 | 0.135420 | -0.177728 | 0.102636 |
| N_RDATE_20 | 0.196260 | 0.522406 | 0.197659 | -0.048980 | -0.134160 | 0.200732 | -0.403441 | 0.134498 | 0.189046 | -0.125713 | 0.381424 | 0.038779 | -0.263701 | 0.028553 | -0.148231 | -0.012426 | 0.102988 | 0.103266 | 0.216872 |
| N_RDATE_21 | 0.209394 | 0.466147 | 0.077242 | -0.021300 | 0.085888 | 0.007962 | 0.067790 | 0.301093 | 0.194156 | -0.036561 | -0.435979 | 0.046504 | 0.529521 | -0.080653 | 0.143557 | -0.071449 | -0.053459 | 0.124816 | 0.050351 |
| N_RDATE_22 | 0.573419 | -0.394140 | -0.047508 | -0.006477 | -0.016287 | -0.181839 | 0.166429 | -0.284621 | -0.229273 | -0.000140 | -0.097579 | 0.081381 | -0.175233 | 0.049220 | 0.025919 | -0.268422 | -0.028719 | 0.269976 | 0.204521 |
| N_RDATE_23 | 0.681452 | 0.023372 | 0.106800 | -0.034633 | -0.001438 | 0.045826 | -0.146182 | 0.083539 | -0.034424 | 0.201610 | 0.111890 | -0.117519 | -0.036064 | 0.094317 | 0.196874 | -0.044098 | -0.540256 | -0.265308 | 0.023887 |
| N_RDATE_24 | 0.723349 | -0.051046 | 0.040462 | -0.008911 | -0.039281 | 0.020951 | -0.117926 | 0.067198 | 0.004118 | 0.094147 | 0.141213 | -0.166663 | 0.041465 | 0.130648 | 0.110952 | 0.088543 | 0.126503 | 0.324964 | -0.469638 |
| RAMNT_3 | -0.087725 | 0.017698 | -0.008984 | 0.005413 | -0.348437 | -0.718020 | -0.029335 | 0.284152 | 0.037262 | 0.289398 | 0.170486 | 0.046253 | -0.032587 | -0.382862 | 0.001222 | 0.007057 | -0.012366 | 0.033161 | -0.013895 |
| RAMNT_4 | -0.107592 | -0.005491 | -0.030524 | 0.011991 | -0.193883 | -0.385476 | -0.029564 | 0.112238 | 0.060501 | 0.035025 | -0.058140 | 0.012081 | 0.133685 | 0.822078 | -0.208979 | 0.079043 | 0.014830 | -0.049514 | 0.068130 |
| RAMNT_5 | 0.001840 | -0.002492 | 0.094342 | -0.001482 | 0.044124 | -0.042552 | -0.343679 | 0.000004 | -0.252362 | 0.323490 | -0.661674 | 0.001308 | -0.234855 | 0.044760 | -0.145697 | -0.000399 | 0.272021 | 0.000156 | -0.064754 |
| RAMNT_6 | 0.014434 | 0.034430 | -0.422572 | -0.897342 | -0.099237 | 0.062647 | 0.001485 | 0.016059 | -0.002634 | 0.024586 | -0.001202 | 0.011024 | 0.005126 | -0.000068 | -0.002109 | 0.001309 | 0.000720 | -0.003620 | -0.001725 |
| RAMNT_7 | 0.052946 | -0.249858 | -0.010075 | 0.058479 | -0.516644 | 0.107957 | -0.098644 | 0.450936 | -0.142328 | -0.487608 | -0.294106 | 0.036255 | -0.184428 | -0.011545 | 0.037823 | -0.096386 | -0.031925 | -0.046812 | -0.054937 |
| RAMNT_8 | 0.260289 | 0.249354 | -0.265235 | 0.030612 | 0.462498 | -0.454415 | -0.108554 | -0.134827 | 0.215862 | -0.401937 | 0.047404 | 0.121871 | -0.086978 | 0.000684 | 0.027154 | -0.095094 | -0.021853 | -0.066076 | -0.054737 |
| RAMNT_9 | 0.025814 | 0.074632 | 0.713697 | -0.337272 | -0.067973 | -0.165422 | 0.096402 | -0.248908 | -0.213974 | -0.047660 | -0.100277 | -0.035886 | 0.017395 | -0.030758 | 0.047445 | 0.355264 | 0.078117 | -0.082860 | 0.045897 |
| RAMNT_10 | -0.192976 | -0.431940 | 0.039274 | -0.069242 | 0.363825 | -0.005672 | -0.339415 | 0.303995 | -0.233720 | 0.102097 | 0.137810 | -0.364471 | 0.259491 | -0.054951 | -0.222963 | -0.153904 | 0.115700 | -0.069547 | 0.093794 |
| RAMNT_11 | -0.029801 | -0.258032 | -0.042317 | 0.055860 | -0.357455 | 0.091948 | -0.255452 | -0.399990 | 0.621909 | 0.236598 | -0.204443 | -0.142015 | 0.079795 | -0.063491 | -0.087295 | -0.076338 | 0.012251 | -0.028997 | 0.025878 |
| RAMNT_12 | 0.049069 | 0.449648 | -0.251205 | 0.179027 | -0.319640 | 0.134053 | 0.484666 | -0.065300 | -0.233226 | 0.103507 | 0.276466 | -0.247117 | 0.163288 | 0.019620 | -0.110579 | -0.155317 | 0.036725 | -0.032869 | 0.051836 |
| RAMNT_13 | -0.563712 | 0.020865 | 0.028344 | -0.022383 | 0.001762 | -0.050530 | 0.026226 | 0.023602 | 0.074859 | 0.061227 | 0.080915 | -0.151882 | -0.171273 | 0.178030 | 0.631785 | -0.209793 | 0.222733 | -0.185010 | -0.075529 |
| RAMNT_14 | -0.259149 | 0.207523 | -0.093984 | 0.080420 | -0.014026 | 0.114598 | -0.401614 | -0.068978 | -0.389031 | 0.406942 | -0.155955 | 0.550020 | -0.001342 | 0.062801 | -0.001102 | -0.081513 | 0.007922 | 0.014849 | -0.113224 |
| RAMNT_15 | -0.691045 | 0.059270 | -0.072038 | 0.020116 | -0.033372 | -0.042635 | -0.026979 | -0.175359 | -0.067916 | -0.212483 | 0.031386 | -0.125752 | -0.034064 | -0.046365 | -0.216992 | 0.086094 | -0.366810 | 0.048311 | -0.317908 |
| RAMNT_16 | -0.320661 | -0.245134 | 0.072161 | -0.044275 | 0.232350 | 0.151707 | 0.391064 | 0.395426 | 0.334221 | 0.218776 | 0.101848 | 0.209057 | -0.223249 | 0.088722 | -0.018161 | 0.153532 | -0.180642 | 0.242175 | 0.058409 |
| RAMNT_17 | -0.256137 | -0.290679 | -0.039540 | 0.021647 | -0.179775 | 0.028365 | -0.149817 | -0.132217 | -0.017393 | -0.283785 | 0.457843 | 0.227971 | 0.460522 | 0.019223 | 0.308073 | 0.107416 | -0.141018 | 0.212691 | 0.156899 |
| RAMNT_18 | -0.355857 | 0.245869 | -0.158841 | 0.054435 | 0.054918 | -0.092187 | -0.251222 | -0.020938 | -0.159497 | 0.049439 | -0.274204 | -0.450857 | -0.189434 | 0.040453 | 0.182564 | 0.165286 | -0.136417 | 0.386214 | 0.248545 |
| RAMNT_19 | -0.314114 | 0.119297 | 0.586255 | -0.280259 | -0.014217 | -0.079228 | 0.062208 | -0.080154 | 0.035205 | -0.069803 | 0.036772 | -0.012644 | 0.046055 | 0.061128 | -0.109189 | -0.540102 | -0.110784 | 0.166058 | -0.092976 |
| RAMNT_20 | -0.190510 | -0.517031 | -0.201420 | 0.049742 | 0.140360 | -0.205446 | 0.404399 | -0.125604 | -0.175485 | 0.126475 | -0.382065 | -0.043071 | 0.272308 | -0.019383 | 0.140395 | 0.018249 | -0.106258 | -0.105785 | -0.214248 |
| RAMNT_21 | -0.205300 | -0.454238 | -0.078968 | 0.022037 | -0.087522 | -0.006040 | -0.067474 | -0.299474 | -0.194435 | 0.026443 | 0.446663 | -0.060075 | -0.525112 | 0.075559 | -0.163328 | 0.074206 | 0.044463 | -0.130356 | -0.072232 |
| RAMNT_22 | -0.543770 | 0.356085 | 0.047197 | 0.005944 | 0.009735 | 0.187693 | -0.169412 | 0.285466 | 0.243775 | -0.010486 | 0.102411 | -0.085003 | 0.187585 | -0.050036 | -0.042181 | 0.278330 | 0.045276 | -0.282764 | -0.224023 |
| RAMNT_23 | -0.640081 | -0.048625 | -0.103608 | 0.033425 | -0.008491 | -0.045099 | 0.140787 | -0.075485 | 0.045451 | -0.210785 | -0.105448 | 0.121816 | 0.044723 | -0.081996 | -0.211186 | 0.046424 | 0.573015 | 0.284862 | -0.034305 |
| RAMNT_24 | -0.679537 | 0.021488 | -0.044826 | 0.010584 | 0.032225 | -0.019822 | 0.120926 | -0.065214 | 0.000207 | -0.103783 | -0.150060 | 0.177379 | -0.041817 | -0.136465 | -0.129349 | -0.090237 | -0.132529 | -0.341012 | 0.504481 |
dic['print_df_pca7'] #RESPONSE TO OTHER TYPES OF MAIL ORDERS
| PC0 | PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | |
|---|---|---|---|---|---|---|---|---|---|
| HIT | -0.739986 | -0.273127 | -0.128543 | 0.068867 | -0.022163 | -0.090798 | -0.242379 | 0.091670 | 0.042771 |
| MBCRAFT | -0.213934 | 0.122194 | -0.559755 | -0.353244 | -0.036572 | -0.263933 | -0.482687 | -0.410746 | -0.124033 |
| MBGARDEN | -0.138010 | 0.639056 | -0.468065 | -0.058502 | 0.080866 | -0.142671 | 0.164833 | 0.491989 | -0.212566 |
| MBBOOKS | -0.957845 | -0.070599 | 0.131760 | 0.072310 | -0.044449 | -0.021799 | -0.094289 | -0.002513 | -0.105491 |
| MBCOLECT | 0.156872 | -0.241714 | -0.281980 | 0.129494 | -0.277434 | 0.829266 | -0.177399 | 0.042290 | 0.021501 |
| MAGFAML | -0.457961 | -0.424325 | -0.260845 | -0.291227 | 0.080150 | -0.194105 | -0.056090 | 0.183209 | 0.416072 |
| MAGFEM | -0.338622 | -0.387561 | -0.011801 | -0.616172 | -0.261237 | -0.029547 | 0.441825 | -0.059882 | 0.150873 |
| MAGMALE | 0.107432 | -0.305328 | 0.221134 | -0.138752 | 0.892234 | 0.122624 | -0.051631 | -0.033840 | -0.024892 |
| PUBGARDN | -0.706470 | 0.528320 | 0.177989 | 0.125310 | 0.039267 | 0.123720 | 0.059340 | -0.173605 | 0.296296 |
| PUBCULIN | -0.765457 | -0.041786 | 0.266395 | -0.156548 | -0.185995 | 0.101194 | 0.077689 | -0.041147 | -0.243134 |
| PUBHLTH | -0.817781 | -0.225290 | 0.293451 | -0.039303 | 0.001124 | 0.014154 | -0.081719 | 0.105801 | -0.300187 |
| PUBDOITY | -0.721248 | 0.588301 | -0.012062 | 0.149247 | 0.093990 | 0.045058 | -0.002107 | -0.063478 | 0.170786 |
| PUBNEWFN | -0.470802 | -0.533849 | -0.111580 | 0.340019 | -0.009995 | -0.123391 | -0.173388 | 0.332206 | 0.203938 |
| PUBPHOTO | 0.590767 | 0.124031 | 0.556270 | 0.014979 | -0.314675 | -0.317853 | -0.275674 | 0.112651 | 0.096592 |
| PUBOPP | -0.087293 | -0.427093 | -0.244486 | 0.652950 | -0.042040 | -0.314224 | 0.317660 | -0.290243 | -0.098418 |
dic['print_df_pca8'] #SUMMARY VARIABLES OF GIVING HISTORY
| PC0 | PC1 | PC2 | PC3 | PC4 | |
|---|---|---|---|---|---|
| RAMNTALL | -0.650556 | -0.671936 | -0.267071 | 0.044757 | 0.184506 |
| NGIFTALL | -0.968004 | -0.021448 | -0.214536 | 0.013054 | 0.055855 |
| CARDGIFT | -0.974643 | 0.029416 | -0.176489 | -0.008022 | 0.035170 |
| MINRAMNT | 0.963035 | -0.149033 | -0.061708 | 0.060907 | -0.140375 |
| N_MINRDATE | -0.929027 | -0.092466 | 0.137762 | -0.267460 | -0.121476 |
| MAXRAMNT | 0.413484 | -0.862440 | -0.075902 | 0.017811 | 0.202336 |
| N_MAXRDATE | -0.818261 | 0.059506 | -0.010329 | 0.520814 | -0.158719 |
| LASTGIFT | 0.659975 | -0.704640 | 0.067369 | -0.124200 | -0.127497 |
| N_LASTDATE | 0.206607 | 0.271218 | 0.888838 | 0.068841 | 0.265067 |
| N_FISTDATE | -0.987991 | -0.059371 | -0.012596 | -0.084863 | -0.076162 |
| N_NEXTDATE | 0.812079 | 0.485822 | -0.294989 | -0.077898 | 0.038115 |
| TIMELAG | 0.879731 | 0.403964 | -0.231755 | -0.045496 | 0.045376 |
| AVGGIFT | 0.788347 | -0.609283 | -0.046164 | 0.037069 | -0.036821 |
dic['most_important_names9'].append('NUMPROM')#Adding the second most relevant component as per the inertia
dic['print_df_pca9'] #SUMMARY VARIABLES OF PROMOTION HISTORY
| PC0 | |
|---|---|
| CARDPROM | -0.945117 |
| N_MAXADATE | 0.931383 |
| NUMPROM | -0.976514 |
| CARDPM12 | -0.387326 |
| NUMPRM12 | -0.410082 |
def apply_mfa(df,columns,name):#multiple factor analysis for categorical data
mfa=prince.MFA(groups={name:columns}, n_components=len(pd.get_dummies(df[columns]).columns.tolist()), n_iter=5, copy=True, check_input=True, engine='auto', random_state=5)
mfa.fit_transform(df[columns])
df_corr=mfa.column_correlations(df[columns])
df_corr.columns=[f'PC{i}' for i in range(mfa.n_components)]
return mfa, df_corr
def apply_famd(df,columns):#factor analysis of mixed data
famd=prince.FAMD(n_components=len(pd.get_dummies(df.loc[:,columns]).columns.tolist()), n_iter=5, copy=True, check_input=True, engine='auto', random_state=5)
famd.fit_transform(df[columns])
df_corr=famd.column_correlations(df[columns])
df_corr.columns=[f'PC{i}' for i in range(famd.n_components)]
return famd, df_corr
def get_inertia_prince(name,ptype,pfeat,variance):
cum=[]
for i in range(len(ptype.explained_inertia_)):
if i==0:
cum.append(ptype.explained_inertia_[i]*100)
else:
cum.append(cum[i-1]+ptype.explained_inertia_[i]*100)
print('Component PC{}, Cumulative Explained Ratio {}'.format(i,np.round(cum[i],2)))
if cum[i]<=variance: n_components=i
return n_components,pd.DataFrame({name:np.round(ptype.explained_inertia_*100,3),'cum_inertia':np.array(cum)},index=pfeat)
def get_feat_names(df,components,trigger=0.45):
farray=[]
for i in range(components):
amax=np.sort(np.abs(df.iloc[:,i]))[::-1][0:2]
for nmax in amax:
nidxm=df.index[np.abs(df.iloc[:,i])==nmax][0]
if nidxm not in farray:
farray.append(nidxm)
else:
nval=np.sort(np.abs(df.iloc[:,i]))[::-1][1]
nidx=df.index[np.abs(df.iloc[:,i])==nval][0]
if nidx not in farray and nval>=trigger:
farray.append(nidx)
return farray
group['Var'][2]=group['Var'][2].replace('ZIP,','')
for i in [0,2,3,5,6]:
print('\nGroup: '+str.upper(group.loc[i,'Group'])+'\n')
if i!=3:
dic['famd'+str(i)],dic['df_corr'+str(i)]=apply_famd(data_ss,group.loc[i,'Var'].split(','))
dic['n_components'+str(i)],dic['famd_df'+str(i)]=get_inertia_prince('df'+str(i),dic['famd'+str(i)],list(dic['df_corr'+str(i)].columns),80)
else:
dic['mfa'+str(i)],dic['df_corr'+str(i)]=apply_mfa(data_ss,group.loc[i,'Var'].split(','),'df'+str(i))
dic['n_components'+str(i)],dic['mfa_df'+str(i)]=get_inertia_prince('df'+str(i),dic['mfa'+str(i)],list(dic['df_corr'+str(i)].columns),80)
dic['most_important_names'+str(i)]=get_feat_names(dic['df_corr'+str(i)].dropna(),dic['n_components'+str(i)])
dic['df_corr'+str(i)]=dic['df_corr'+str(i)].style.applymap(color_pca_red_green)
print('\nList of most relevant features:\n',dic['most_important_names'+str(i)])
Group: RFA (RECENCY-FREQUENCY-DONATION AMOUNT) Component PC0, Cumulative Explained Ratio 21.92 Component PC1, Cumulative Explained Ratio 39.46 Component PC2, Cumulative Explained Ratio 49.61 Component PC3, Cumulative Explained Ratio 56.28 Component PC4, Cumulative Explained Ratio 62.93 Component PC5, Cumulative Explained Ratio 69.01 Component PC6, Cumulative Explained Ratio 75.06 Component PC7, Cumulative Explained Ratio 80.71 Component PC8, Cumulative Explained Ratio 86.05 Component PC9, Cumulative Explained Ratio 90.62 Component PC10, Cumulative Explained Ratio 94.33 Component PC11, Cumulative Explained Ratio 97.87 Component PC12, Cumulative Explained Ratio 100.0 Component PC13, Cumulative Explained Ratio 100.0 Component PC14, Cumulative Explained Ratio 100.0 Component PC15, Cumulative Explained Ratio 100.0 Component PC16, Cumulative Explained Ratio 100.0 Component PC17, Cumulative Explained Ratio 100.0 Component PC18, Cumulative Explained Ratio 100.0 List of most relevant features: ['RFA_2F', 'RFA_2A_D', 'MDMAUD_F_5', 'MDMAUD_R_D'] Group: DEMOGRAPHICS Component PC0, Cumulative Explained Ratio 0.73 Component PC1, Cumulative Explained Ratio 1.26 Component PC2, Cumulative Explained Ratio 1.74 Component PC3, Cumulative Explained Ratio 2.15 Component PC4, Cumulative Explained Ratio 2.51 Component PC5, Cumulative Explained Ratio 2.87 Component PC6, Cumulative Explained Ratio 3.13 Component PC7, Cumulative Explained Ratio 3.34 Component PC8, Cumulative Explained Ratio 3.54 Component PC9, Cumulative Explained Ratio 3.74 Component PC10, Cumulative Explained Ratio 3.93 Component PC11, Cumulative Explained Ratio 4.1 Component PC12, Cumulative Explained Ratio 4.26 Component PC13, Cumulative Explained Ratio 4.41 Component PC14, Cumulative Explained Ratio 4.56 Component PC15, Cumulative Explained Ratio 4.71 Component PC16, Cumulative Explained Ratio 4.84 Component PC17, Cumulative Explained Ratio 4.96 Component PC18, Cumulative Explained Ratio 5.09 Component PC19, Cumulative Explained Ratio 5.21 Component PC20, Cumulative Explained Ratio 5.34 Component PC21, Cumulative Explained Ratio 5.46 Component PC22, Cumulative Explained Ratio 5.58 Component PC23, Cumulative Explained Ratio 5.69 Component PC24, Cumulative Explained Ratio 5.81 Component PC25, Cumulative Explained Ratio 5.92 Component PC26, Cumulative Explained Ratio 6.04 Component PC27, Cumulative Explained Ratio 6.15 Component PC28, Cumulative Explained Ratio 6.27 Component PC29, Cumulative Explained Ratio 6.38 Component PC30, Cumulative Explained Ratio 6.49 Component PC31, Cumulative Explained Ratio 6.61 Component PC32, Cumulative Explained Ratio 6.72 Component PC33, Cumulative Explained Ratio 6.83 Component PC34, Cumulative Explained Ratio 6.94 Component PC35, Cumulative Explained Ratio 7.06 Component PC36, Cumulative Explained Ratio 7.17 Component PC37, Cumulative Explained Ratio 7.28 Component PC38, Cumulative Explained Ratio 7.39 Component PC39, Cumulative Explained Ratio 7.5 Component PC40, Cumulative Explained Ratio 7.61 Component PC41, Cumulative Explained Ratio 7.72 Component PC42, Cumulative Explained Ratio 7.83 Component PC43, Cumulative Explained Ratio 7.95 Component PC44, Cumulative Explained Ratio 8.06 Component PC45, Cumulative Explained Ratio 8.17 Component PC46, Cumulative Explained Ratio 8.28 Component PC47, Cumulative Explained Ratio 8.39 Component PC48, Cumulative Explained Ratio 8.5 Component PC49, Cumulative Explained Ratio 8.6 Component PC50, Cumulative Explained Ratio 8.71 Component PC51, Cumulative Explained Ratio 8.82 Component PC52, Cumulative Explained Ratio 8.93 Component PC53, Cumulative Explained Ratio 9.04 Component PC54, Cumulative Explained Ratio 9.15 Component PC55, Cumulative Explained Ratio 9.26 Component PC56, Cumulative Explained Ratio 9.37 Component PC57, Cumulative Explained Ratio 9.48 Component PC58, Cumulative Explained Ratio 9.58 Component PC59, Cumulative Explained Ratio 9.69 Component PC60, Cumulative Explained Ratio 9.8 Component PC61, Cumulative Explained Ratio 9.91 Component PC62, Cumulative Explained Ratio 10.01 Component PC63, Cumulative Explained Ratio 10.12 Component PC64, Cumulative Explained Ratio 10.23 Component PC65, Cumulative Explained Ratio 10.34 Component PC66, Cumulative Explained Ratio 10.44 Component PC67, Cumulative Explained Ratio 10.55 Component PC68, Cumulative Explained Ratio 10.66 Component PC69, Cumulative Explained Ratio 10.76 Component PC70, Cumulative Explained Ratio 10.87 Component PC71, Cumulative Explained Ratio 10.98 Component PC72, Cumulative Explained Ratio 11.08 Component PC73, Cumulative Explained Ratio 11.19 Component PC74, Cumulative Explained Ratio 11.3 Component PC75, Cumulative Explained Ratio 11.4 Component PC76, Cumulative Explained Ratio 11.51 Component PC77, Cumulative Explained Ratio 11.61 Component PC78, Cumulative Explained Ratio 11.72 Component PC79, Cumulative Explained Ratio 11.82 Component PC80, Cumulative Explained Ratio 11.93 Component PC81, Cumulative Explained Ratio 12.03 Component PC82, Cumulative Explained Ratio 12.14 Component PC83, Cumulative Explained Ratio 12.24 Component PC84, Cumulative Explained Ratio 12.34 Component PC85, Cumulative Explained Ratio 12.45 Component PC86, Cumulative Explained Ratio 12.55 Component PC87, Cumulative Explained Ratio 12.66 Component PC88, Cumulative Explained Ratio 12.76 Component PC89, Cumulative Explained Ratio 12.86 Component PC90, Cumulative Explained Ratio 12.96 Component PC91, Cumulative Explained Ratio 13.07 Component PC92, Cumulative Explained Ratio 13.17 Component PC93, Cumulative Explained Ratio 13.27 Component PC94, Cumulative Explained Ratio 13.37 Component PC95, Cumulative Explained Ratio 13.47 Component PC96, Cumulative Explained Ratio 13.58 Component PC97, Cumulative Explained Ratio 13.68 Component PC98, Cumulative Explained Ratio 13.78 Component PC99, Cumulative Explained Ratio 13.88 Component PC100, Cumulative Explained Ratio 13.98 Component PC101, Cumulative Explained Ratio 14.08 Component PC102, Cumulative Explained Ratio 14.18 Component PC103, Cumulative Explained Ratio 14.28 Component PC104, Cumulative Explained Ratio 14.38 Component PC105, Cumulative Explained Ratio 14.47 Component PC106, Cumulative Explained Ratio 14.57 Component PC107, Cumulative Explained Ratio 14.67 Component PC108, Cumulative Explained Ratio 14.77 Component PC109, Cumulative Explained Ratio 14.87 Component PC110, Cumulative Explained Ratio 14.97 Component PC111, Cumulative Explained Ratio 15.07 Component PC112, Cumulative Explained Ratio 15.17 Component PC113, Cumulative Explained Ratio 15.27 Component PC114, Cumulative Explained Ratio 15.37 Component PC115, Cumulative Explained Ratio 15.47 Component PC116, Cumulative Explained Ratio 15.56 Component PC117, Cumulative Explained Ratio 15.66 Component PC118, Cumulative Explained Ratio 15.76 Component PC119, Cumulative Explained Ratio 15.86 Component PC120, Cumulative Explained Ratio 15.96 Component PC121, Cumulative Explained Ratio 16.06 Component PC122, Cumulative Explained Ratio 16.16 Component PC123, Cumulative Explained Ratio 16.26 Component PC124, Cumulative Explained Ratio 16.36 Component PC125, Cumulative Explained Ratio 16.45 Component PC126, Cumulative Explained Ratio 16.55 Component PC127, Cumulative Explained Ratio 16.65 Component PC128, Cumulative Explained Ratio 16.75 Component PC129, Cumulative Explained Ratio 16.85 Component PC130, Cumulative Explained Ratio 16.95 Component PC131, Cumulative Explained Ratio 17.05 Component PC132, Cumulative Explained Ratio 17.14 Component PC133, Cumulative Explained Ratio 17.24 Component PC134, Cumulative Explained Ratio 17.34 Component PC135, Cumulative Explained Ratio 17.44 Component PC136, Cumulative Explained Ratio 17.54 Component PC137, Cumulative Explained Ratio 17.64 Component PC138, Cumulative Explained Ratio 17.74 Component PC139, Cumulative Explained Ratio 17.84 Component PC140, Cumulative Explained Ratio 17.93 Component PC141, Cumulative Explained Ratio 18.03 Component PC142, Cumulative Explained Ratio 18.13 Component PC143, Cumulative Explained Ratio 18.23 Component PC144, Cumulative Explained Ratio 18.33 Component PC145, Cumulative Explained Ratio 18.43 Component PC146, Cumulative Explained Ratio 18.53 Component PC147, Cumulative Explained Ratio 18.62 Component PC148, Cumulative Explained Ratio 18.72 Component PC149, Cumulative Explained Ratio 18.82 Component PC150, Cumulative Explained Ratio 18.92 Component PC151, Cumulative Explained Ratio 19.02 Component PC152, Cumulative Explained Ratio 19.12 Component PC153, Cumulative Explained Ratio 19.21 Component PC154, Cumulative Explained Ratio 19.31 Component PC155, Cumulative Explained Ratio 19.41 Component PC156, Cumulative Explained Ratio 19.51 Component PC157, Cumulative Explained Ratio 19.61 Component PC158, Cumulative Explained Ratio 19.71 Component PC159, Cumulative Explained Ratio 19.81 Component PC160, Cumulative Explained Ratio 19.9 Component PC161, Cumulative Explained Ratio 20.0 Component PC162, Cumulative Explained Ratio 20.1 Component PC163, Cumulative Explained Ratio 20.2 Component PC164, Cumulative Explained Ratio 20.3 Component PC165, Cumulative Explained Ratio 20.4 Component PC166, Cumulative Explained Ratio 20.5 Component PC167, Cumulative Explained Ratio 20.59 Component PC168, Cumulative Explained Ratio 20.69 Component PC169, Cumulative Explained Ratio 20.79 Component PC170, Cumulative Explained Ratio 20.89 Component PC171, Cumulative Explained Ratio 20.99 Component PC172, Cumulative Explained Ratio 21.09 Component PC173, Cumulative Explained Ratio 21.18 Component PC174, Cumulative Explained Ratio 21.28 Component PC175, Cumulative Explained Ratio 21.38 Component PC176, Cumulative Explained Ratio 21.48 Component PC177, Cumulative Explained Ratio 21.58 Component PC178, Cumulative Explained Ratio 21.68 Component PC179, Cumulative Explained Ratio 21.78 Component PC180, Cumulative Explained Ratio 21.87 Component PC181, Cumulative Explained Ratio 21.97 Component PC182, Cumulative Explained Ratio 22.07 Component PC183, Cumulative Explained Ratio 22.17 Component PC184, Cumulative Explained Ratio 22.27 Component PC185, Cumulative Explained Ratio 22.37 Component PC186, Cumulative Explained Ratio 22.46 Component PC187, Cumulative Explained Ratio 22.56 Component PC188, Cumulative Explained Ratio 22.66 Component PC189, Cumulative Explained Ratio 22.76 Component PC190, Cumulative Explained Ratio 22.86 Component PC191, Cumulative Explained Ratio 22.96 Component PC192, Cumulative Explained Ratio 23.05 Component PC193, Cumulative Explained Ratio 23.15 Component PC194, Cumulative Explained Ratio 23.25 Component PC195, Cumulative Explained Ratio 23.35 Component PC196, Cumulative Explained Ratio 23.45 Component PC197, Cumulative Explained Ratio 23.55 Component PC198, Cumulative Explained Ratio 23.65 Component PC199, Cumulative Explained Ratio 23.74 Component PC200, Cumulative Explained Ratio 23.84 Component PC201, Cumulative Explained Ratio 23.94 Component PC202, Cumulative Explained Ratio 24.04 Component PC203, Cumulative Explained Ratio 24.14 Component PC204, Cumulative Explained Ratio 24.24 Component PC205, Cumulative Explained Ratio 24.33 Component PC206, Cumulative Explained Ratio 24.43 Component PC207, Cumulative Explained Ratio 24.53 Component PC208, Cumulative Explained Ratio 24.63 Component PC209, Cumulative Explained Ratio 24.73 Component PC210, Cumulative Explained Ratio 24.83 Component PC211, Cumulative Explained Ratio 24.92 Component PC212, Cumulative Explained Ratio 25.02 Component PC213, Cumulative Explained Ratio 25.12 Component PC214, Cumulative Explained Ratio 25.22 Component PC215, Cumulative Explained Ratio 25.32 Component PC216, Cumulative Explained Ratio 25.42 Component PC217, Cumulative Explained Ratio 25.52 Component PC218, Cumulative Explained Ratio 25.61 Component PC219, Cumulative Explained Ratio 25.71 Component PC220, Cumulative Explained Ratio 25.81 Component PC221, Cumulative Explained Ratio 25.91 Component PC222, Cumulative Explained Ratio 26.01 Component PC223, Cumulative Explained Ratio 26.11 Component PC224, Cumulative Explained Ratio 26.2 Component PC225, Cumulative Explained Ratio 26.3 Component PC226, Cumulative Explained Ratio 26.4 Component PC227, Cumulative Explained Ratio 26.5 Component PC228, Cumulative Explained Ratio 26.6 Component PC229, Cumulative Explained Ratio 26.7 Component PC230, Cumulative Explained Ratio 26.79 Component PC231, Cumulative Explained Ratio 26.89 Component PC232, Cumulative Explained Ratio 26.99 Component PC233, Cumulative Explained Ratio 27.09 Component PC234, Cumulative Explained Ratio 27.19 Component PC235, Cumulative Explained Ratio 27.29 Component PC236, Cumulative Explained Ratio 27.38 Component PC237, Cumulative Explained Ratio 27.48 Component PC238, Cumulative Explained Ratio 27.58 Component PC239, Cumulative Explained Ratio 27.68 Component PC240, Cumulative Explained Ratio 27.78 Component PC241, Cumulative Explained Ratio 27.88 Component PC242, Cumulative Explained Ratio 27.98 Component PC243, Cumulative Explained Ratio 28.07 Component PC244, Cumulative Explained Ratio 28.17 Component PC245, Cumulative Explained Ratio 28.27 Component PC246, Cumulative Explained Ratio 28.37 Component PC247, Cumulative Explained Ratio 28.47 Component PC248, Cumulative Explained Ratio 28.57 Component PC249, Cumulative Explained Ratio 28.66 Component PC250, Cumulative Explained Ratio 28.76 Component PC251, Cumulative Explained Ratio 28.86 Component PC252, Cumulative Explained Ratio 28.96 Component PC253, Cumulative Explained Ratio 29.06 Component PC254, Cumulative Explained Ratio 29.16 Component PC255, Cumulative Explained Ratio 29.25 Component PC256, Cumulative Explained Ratio 29.35 Component PC257, Cumulative Explained Ratio 29.45 Component PC258, Cumulative Explained Ratio 29.55 Component PC259, Cumulative Explained Ratio 29.65 Component PC260, Cumulative Explained Ratio 29.75 Component PC261, Cumulative Explained Ratio 29.84 Component PC262, Cumulative Explained Ratio 29.94 Component PC263, Cumulative Explained Ratio 30.04 Component PC264, Cumulative Explained Ratio 30.14 Component PC265, Cumulative Explained Ratio 30.24 Component PC266, Cumulative Explained Ratio 30.34 Component PC267, Cumulative Explained Ratio 30.43 Component PC268, Cumulative Explained Ratio 30.53 Component PC269, Cumulative Explained Ratio 30.63 Component PC270, Cumulative Explained Ratio 30.73 Component PC271, Cumulative Explained Ratio 30.83 Component PC272, Cumulative Explained Ratio 30.93 Component PC273, Cumulative Explained Ratio 31.02 Component PC274, Cumulative Explained Ratio 31.12 Component PC275, Cumulative Explained Ratio 31.22 Component PC276, Cumulative Explained Ratio 31.32 Component PC277, Cumulative Explained Ratio 31.42 Component PC278, Cumulative Explained Ratio 31.52 Component PC279, Cumulative Explained Ratio 31.61 Component PC280, Cumulative Explained Ratio 31.71 Component PC281, Cumulative Explained Ratio 31.81 Component PC282, Cumulative Explained Ratio 31.91 Component PC283, Cumulative Explained Ratio 32.01 Component PC284, Cumulative Explained Ratio 32.11 Component PC285, Cumulative Explained Ratio 32.21 Component PC286, Cumulative Explained Ratio 32.3 Component PC287, Cumulative Explained Ratio 32.4 Component PC288, Cumulative Explained Ratio 32.5 Component PC289, Cumulative Explained Ratio 32.6 Component PC290, Cumulative Explained Ratio 32.7 Component PC291, Cumulative Explained Ratio 32.8 Component PC292, Cumulative Explained Ratio 32.89 Component PC293, Cumulative Explained Ratio 32.99 Component PC294, Cumulative Explained Ratio 33.09 Component PC295, Cumulative Explained Ratio 33.19 Component PC296, Cumulative Explained Ratio 33.29 Component PC297, Cumulative Explained Ratio 33.39 Component PC298, Cumulative Explained Ratio 33.48 Component PC299, Cumulative Explained Ratio 33.58 Component PC300, Cumulative Explained Ratio 33.68 Component PC301, Cumulative Explained Ratio 33.78 Component PC302, Cumulative Explained Ratio 33.88 Component PC303, Cumulative Explained Ratio 33.98 Component PC304, Cumulative Explained Ratio 34.07 Component PC305, Cumulative Explained Ratio 34.17 Component PC306, Cumulative Explained Ratio 34.27 Component PC307, Cumulative Explained Ratio 34.37 Component PC308, Cumulative Explained Ratio 34.47 Component PC309, Cumulative Explained Ratio 34.57 Component PC310, Cumulative Explained Ratio 34.66 Component PC311, Cumulative Explained Ratio 34.76 Component PC312, Cumulative Explained Ratio 34.86 Component PC313, Cumulative Explained Ratio 34.96 Component PC314, Cumulative Explained Ratio 35.06 Component PC315, Cumulative Explained Ratio 35.16 Component PC316, Cumulative Explained Ratio 35.25 Component PC317, Cumulative Explained Ratio 35.35 Component PC318, Cumulative Explained Ratio 35.45 Component PC319, Cumulative Explained Ratio 35.55 Component PC320, Cumulative Explained Ratio 35.65 Component PC321, Cumulative Explained Ratio 35.75 Component PC322, Cumulative Explained Ratio 35.84 Component PC323, Cumulative Explained Ratio 35.94 Component PC324, Cumulative Explained Ratio 36.04 Component PC325, Cumulative Explained Ratio 36.14 Component PC326, Cumulative Explained Ratio 36.24 Component PC327, Cumulative Explained Ratio 36.34 Component PC328, Cumulative Explained Ratio 36.43 Component PC329, Cumulative Explained Ratio 36.53 Component PC330, Cumulative Explained Ratio 36.63 Component PC331, Cumulative Explained Ratio 36.73 Component PC332, Cumulative Explained Ratio 36.83 Component PC333, Cumulative Explained Ratio 36.93 Component PC334, Cumulative Explained Ratio 37.02 Component PC335, Cumulative Explained Ratio 37.12 Component PC336, Cumulative Explained Ratio 37.22 Component PC337, Cumulative Explained Ratio 37.32 Component PC338, Cumulative Explained Ratio 37.42 Component PC339, Cumulative Explained Ratio 37.52 Component PC340, Cumulative Explained Ratio 37.61 Component PC341, Cumulative Explained Ratio 37.71 Component PC342, Cumulative Explained Ratio 37.81 Component PC343, Cumulative Explained Ratio 37.91 Component PC344, Cumulative Explained Ratio 38.01 Component PC345, Cumulative Explained Ratio 38.11 Component PC346, Cumulative Explained Ratio 38.2 Component PC347, Cumulative Explained Ratio 38.3 Component PC348, Cumulative Explained Ratio 38.4 Component PC349, Cumulative Explained Ratio 38.5 Component PC350, Cumulative Explained Ratio 38.6 Component PC351, Cumulative Explained Ratio 38.7 Component PC352, Cumulative Explained Ratio 38.8 Component PC353, Cumulative Explained Ratio 38.89 Component PC354, Cumulative Explained Ratio 38.99 Component PC355, Cumulative Explained Ratio 39.09 Component PC356, Cumulative Explained Ratio 39.19 Component PC357, Cumulative Explained Ratio 39.29 Component PC358, Cumulative Explained Ratio 39.39 Component PC359, Cumulative Explained Ratio 39.48 Component PC360, Cumulative Explained Ratio 39.58 Component PC361, Cumulative Explained Ratio 39.68 Component PC362, Cumulative Explained Ratio 39.78 Component PC363, Cumulative Explained Ratio 39.88 Component PC364, Cumulative Explained Ratio 39.98 Component PC365, Cumulative Explained Ratio 40.07 Component PC366, Cumulative Explained Ratio 40.17 Component PC367, Cumulative Explained Ratio 40.27 Component PC368, Cumulative Explained Ratio 40.37 Component PC369, Cumulative Explained Ratio 40.47 Component PC370, Cumulative Explained Ratio 40.57 Component PC371, Cumulative Explained Ratio 40.66 Component PC372, Cumulative Explained Ratio 40.76 Component PC373, Cumulative Explained Ratio 40.86 Component PC374, Cumulative Explained Ratio 40.96 Component PC375, Cumulative Explained Ratio 41.06 Component PC376, Cumulative Explained Ratio 41.16 Component PC377, Cumulative Explained Ratio 41.25 Component PC378, Cumulative Explained Ratio 41.35 Component PC379, Cumulative Explained Ratio 41.45 Component PC380, Cumulative Explained Ratio 41.55 Component PC381, Cumulative Explained Ratio 41.65 Component PC382, Cumulative Explained Ratio 41.75 Component PC383, Cumulative Explained Ratio 41.84 Component PC384, Cumulative Explained Ratio 41.94 Component PC385, Cumulative Explained Ratio 42.04 Component PC386, Cumulative Explained Ratio 42.14 Component PC387, Cumulative Explained Ratio 42.24 Component PC388, Cumulative Explained Ratio 42.34 Component PC389, Cumulative Explained Ratio 42.43 Component PC390, Cumulative Explained Ratio 42.53 Component PC391, Cumulative Explained Ratio 42.63 Component PC392, Cumulative Explained Ratio 42.73 Component PC393, Cumulative Explained Ratio 42.83 Component PC394, Cumulative Explained Ratio 42.93 Component PC395, Cumulative Explained Ratio 43.02 Component PC396, Cumulative Explained Ratio 43.12 Component PC397, Cumulative Explained Ratio 43.22 Component PC398, Cumulative Explained Ratio 43.32 Component PC399, Cumulative Explained Ratio 43.42 Component PC400, Cumulative Explained Ratio 43.52 Component PC401, Cumulative Explained Ratio 43.61 Component PC402, Cumulative Explained Ratio 43.71 Component PC403, Cumulative Explained Ratio 43.81 Component PC404, Cumulative Explained Ratio 43.91 Component PC405, Cumulative Explained Ratio 44.01 Component PC406, Cumulative Explained Ratio 44.11 Component PC407, Cumulative Explained Ratio 44.2 Component PC408, Cumulative Explained Ratio 44.3 Component PC409, Cumulative Explained Ratio 44.4 Component PC410, Cumulative Explained Ratio 44.5 Component PC411, Cumulative Explained Ratio 44.6 Component PC412, Cumulative Explained Ratio 44.7 Component PC413, Cumulative Explained Ratio 44.79 Component PC414, Cumulative Explained Ratio 44.89 Component PC415, Cumulative Explained Ratio 44.99 Component PC416, Cumulative Explained Ratio 45.09 Component PC417, Cumulative Explained Ratio 45.19 Component PC418, Cumulative Explained Ratio 45.29 Component PC419, Cumulative Explained Ratio 45.38 Component PC420, Cumulative Explained Ratio 45.48 Component PC421, Cumulative Explained Ratio 45.58 Component PC422, Cumulative Explained Ratio 45.68 Component PC423, Cumulative Explained Ratio 45.78 Component PC424, Cumulative Explained Ratio 45.88 Component PC425, Cumulative Explained Ratio 45.97 Component PC426, Cumulative Explained Ratio 46.07 Component PC427, Cumulative Explained Ratio 46.17 Component PC428, Cumulative Explained Ratio 46.27 Component PC429, Cumulative Explained Ratio 46.37 Component PC430, Cumulative Explained Ratio 46.47 Component PC431, Cumulative Explained Ratio 46.56 Component PC432, Cumulative Explained Ratio 46.66 Component PC433, Cumulative Explained Ratio 46.76 Component PC434, Cumulative Explained Ratio 46.86 Component PC435, Cumulative Explained Ratio 46.96 Component PC436, Cumulative Explained Ratio 47.06 Component PC437, Cumulative Explained Ratio 47.15 Component PC438, Cumulative Explained Ratio 47.25 Component PC439, Cumulative Explained Ratio 47.35 Component PC440, Cumulative Explained Ratio 47.45 Component PC441, Cumulative Explained Ratio 47.55 Component PC442, Cumulative Explained Ratio 47.65 Component PC443, Cumulative Explained Ratio 47.74 Component PC444, Cumulative Explained Ratio 47.84 Component PC445, Cumulative Explained Ratio 47.94 Component PC446, Cumulative Explained Ratio 48.04 Component PC447, Cumulative Explained Ratio 48.14 Component PC448, Cumulative Explained Ratio 48.24 Component PC449, Cumulative Explained Ratio 48.33 Component PC450, Cumulative Explained Ratio 48.43 Component PC451, Cumulative Explained Ratio 48.53 Component PC452, Cumulative Explained Ratio 48.63 Component PC453, Cumulative Explained Ratio 48.73 Component PC454, Cumulative Explained Ratio 48.83 Component PC455, Cumulative Explained Ratio 48.92 Component PC456, Cumulative Explained Ratio 49.02 Component PC457, Cumulative Explained Ratio 49.12 Component PC458, Cumulative Explained Ratio 49.22 Component PC459, Cumulative Explained Ratio 49.32 Component PC460, Cumulative Explained Ratio 49.42 Component PC461, Cumulative Explained Ratio 49.51 Component PC462, Cumulative Explained Ratio 49.61 Component PC463, Cumulative Explained Ratio 49.71 Component PC464, Cumulative Explained Ratio 49.81 Component PC465, Cumulative Explained Ratio 49.91 Component PC466, Cumulative Explained Ratio 50.01 Component PC467, Cumulative Explained Ratio 50.11 Component PC468, Cumulative Explained Ratio 50.2 Component PC469, Cumulative Explained Ratio 50.3 Component PC470, Cumulative Explained Ratio 50.4 Component PC471, Cumulative Explained Ratio 50.5 Component PC472, Cumulative Explained Ratio 50.6 Component PC473, Cumulative Explained Ratio 50.7 Component PC474, Cumulative Explained Ratio 50.79 Component PC475, Cumulative Explained Ratio 50.89 Component PC476, Cumulative Explained Ratio 50.99 Component PC477, Cumulative Explained Ratio 51.09 Component PC478, Cumulative Explained Ratio 51.19 Component PC479, Cumulative Explained Ratio 51.29 Component PC480, Cumulative Explained Ratio 51.38 Component PC481, Cumulative Explained Ratio 51.48 Component PC482, Cumulative Explained Ratio 51.58 Component PC483, Cumulative Explained Ratio 51.68 Component PC484, Cumulative Explained Ratio 51.78 Component PC485, Cumulative Explained Ratio 51.88 Component PC486, Cumulative Explained Ratio 51.97 Component PC487, Cumulative Explained Ratio 52.07 Component PC488, Cumulative Explained Ratio 52.17 Component PC489, Cumulative Explained Ratio 52.27 Component PC490, Cumulative Explained Ratio 52.37 Component PC491, Cumulative Explained Ratio 52.47 Component PC492, Cumulative Explained Ratio 52.56 Component PC493, Cumulative Explained Ratio 52.66 Component PC494, Cumulative Explained Ratio 52.76 Component PC495, Cumulative Explained Ratio 52.86 Component PC496, Cumulative Explained Ratio 52.96 Component PC497, Cumulative Explained Ratio 53.06 Component PC498, Cumulative Explained Ratio 53.15 Component PC499, Cumulative Explained Ratio 53.25 Component PC500, Cumulative Explained Ratio 53.35 Component PC501, Cumulative Explained Ratio 53.45 Component PC502, Cumulative Explained Ratio 53.55 Component PC503, Cumulative Explained Ratio 53.65 Component PC504, Cumulative Explained Ratio 53.74 Component PC505, Cumulative Explained Ratio 53.84 Component PC506, Cumulative Explained Ratio 53.94 Component PC507, Cumulative Explained Ratio 54.04 Component PC508, Cumulative Explained Ratio 54.14 Component PC509, Cumulative Explained Ratio 54.24 Component PC510, Cumulative Explained Ratio 54.33 Component PC511, Cumulative Explained Ratio 54.43 Component PC512, Cumulative Explained Ratio 54.53 Component PC513, Cumulative Explained Ratio 54.63 Component PC514, Cumulative Explained Ratio 54.73 Component PC515, Cumulative Explained Ratio 54.83 Component PC516, Cumulative Explained Ratio 54.92 Component PC517, Cumulative Explained Ratio 55.02 Component PC518, Cumulative Explained Ratio 55.12 Component PC519, Cumulative Explained Ratio 55.22 Component PC520, Cumulative Explained Ratio 55.32 Component PC521, Cumulative Explained Ratio 55.42 Component PC522, Cumulative Explained Ratio 55.51 Component PC523, Cumulative Explained Ratio 55.61 Component PC524, Cumulative Explained Ratio 55.71 Component PC525, Cumulative Explained Ratio 55.81 Component PC526, Cumulative Explained Ratio 55.91 Component PC527, Cumulative Explained Ratio 56.01 Component PC528, Cumulative Explained Ratio 56.1 Component PC529, Cumulative Explained Ratio 56.2 Component PC530, Cumulative Explained Ratio 56.3 Component PC531, Cumulative Explained Ratio 56.4 Component PC532, Cumulative Explained Ratio 56.5 Component PC533, Cumulative Explained Ratio 56.6 Component PC534, Cumulative Explained Ratio 56.69 Component PC535, Cumulative Explained Ratio 56.79 Component PC536, Cumulative Explained Ratio 56.89 Component PC537, Cumulative Explained Ratio 56.99 Component PC538, Cumulative Explained Ratio 57.09 Component PC539, Cumulative Explained Ratio 57.19 Component PC540, Cumulative Explained Ratio 57.28 Component PC541, Cumulative Explained Ratio 57.38 Component PC542, Cumulative Explained Ratio 57.48 Component PC543, Cumulative Explained Ratio 57.58 Component PC544, Cumulative Explained Ratio 57.68 Component PC545, Cumulative Explained Ratio 57.78 Component PC546, Cumulative Explained Ratio 57.87 Component PC547, Cumulative Explained Ratio 57.97 Component PC548, Cumulative Explained Ratio 58.07 Component PC549, Cumulative Explained Ratio 58.17 Component PC550, Cumulative Explained Ratio 58.27 Component PC551, Cumulative Explained Ratio 58.37 Component PC552, Cumulative Explained Ratio 58.46 Component PC553, Cumulative Explained Ratio 58.56 Component PC554, Cumulative Explained Ratio 58.66 Component PC555, Cumulative Explained Ratio 58.76 Component PC556, Cumulative Explained Ratio 58.86 Component PC557, Cumulative Explained Ratio 58.96 Component PC558, Cumulative Explained Ratio 59.05 Component PC559, Cumulative Explained Ratio 59.15 Component PC560, Cumulative Explained Ratio 59.25 Component PC561, Cumulative Explained Ratio 59.35 Component PC562, Cumulative Explained Ratio 59.45 Component PC563, Cumulative Explained Ratio 59.55 Component PC564, Cumulative Explained Ratio 59.64 Component PC565, Cumulative Explained Ratio 59.74 Component PC566, Cumulative Explained Ratio 59.84 Component PC567, Cumulative Explained Ratio 59.94 Component PC568, Cumulative Explained Ratio 60.04 Component PC569, Cumulative Explained Ratio 60.14 Component PC570, Cumulative Explained Ratio 60.23 Component PC571, Cumulative Explained Ratio 60.33 Component PC572, Cumulative Explained Ratio 60.43 Component PC573, Cumulative Explained Ratio 60.53 Component PC574, Cumulative Explained Ratio 60.63 Component PC575, Cumulative Explained Ratio 60.73 Component PC576, Cumulative Explained Ratio 60.82 Component PC577, Cumulative Explained Ratio 60.92 Component PC578, Cumulative Explained Ratio 61.02 Component PC579, Cumulative Explained Ratio 61.12 Component PC580, Cumulative Explained Ratio 61.22 Component PC581, Cumulative Explained Ratio 61.32 Component PC582, Cumulative Explained Ratio 61.41 Component PC583, Cumulative Explained Ratio 61.51 Component PC584, Cumulative Explained Ratio 61.61 Component PC585, Cumulative Explained Ratio 61.71 Component PC586, Cumulative Explained Ratio 61.81 Component PC587, Cumulative Explained Ratio 61.91 Component PC588, Cumulative Explained Ratio 62.0 Component PC589, Cumulative Explained Ratio 62.1 Component PC590, Cumulative Explained Ratio 62.2 Component PC591, Cumulative Explained Ratio 62.3 Component PC592, Cumulative Explained Ratio 62.4 Component PC593, Cumulative Explained Ratio 62.5 Component PC594, Cumulative Explained Ratio 62.59 Component PC595, Cumulative Explained Ratio 62.69 Component PC596, Cumulative Explained Ratio 62.79 Component PC597, Cumulative Explained Ratio 62.89 Component PC598, Cumulative Explained Ratio 62.99 Component PC599, Cumulative Explained Ratio 63.09 Component PC600, Cumulative Explained Ratio 63.18 Component PC601, Cumulative Explained Ratio 63.28 Component PC602, Cumulative Explained Ratio 63.38 Component PC603, Cumulative Explained Ratio 63.48 Component PC604, Cumulative Explained Ratio 63.58 Component PC605, Cumulative Explained Ratio 63.68 Component PC606, Cumulative Explained Ratio 63.77 Component PC607, Cumulative Explained Ratio 63.87 Component PC608, Cumulative Explained Ratio 63.97 Component PC609, Cumulative Explained Ratio 64.07 Component PC610, Cumulative Explained Ratio 64.17 Component PC611, Cumulative Explained Ratio 64.27 Component PC612, Cumulative Explained Ratio 64.36 Component PC613, Cumulative Explained Ratio 64.46 Component PC614, Cumulative Explained Ratio 64.56 Component PC615, Cumulative Explained Ratio 64.66 Component PC616, Cumulative Explained Ratio 64.76 Component PC617, Cumulative Explained Ratio 64.86 Component PC618, Cumulative Explained Ratio 64.96 Component PC619, Cumulative Explained Ratio 65.05 Component PC620, Cumulative Explained Ratio 65.15 Component PC621, Cumulative Explained Ratio 65.25 Component PC622, Cumulative Explained Ratio 65.35 Component PC623, Cumulative Explained Ratio 65.45 Component PC624, Cumulative Explained Ratio 65.55 Component PC625, Cumulative Explained Ratio 65.64 Component PC626, Cumulative Explained Ratio 65.74 Component PC627, Cumulative Explained Ratio 65.84 Component PC628, Cumulative Explained Ratio 65.94 Component PC629, Cumulative Explained Ratio 66.04 Component PC630, Cumulative Explained Ratio 66.14 Component PC631, Cumulative Explained Ratio 66.23 Component PC632, Cumulative Explained Ratio 66.33 Component PC633, Cumulative Explained Ratio 66.43 Component PC634, Cumulative Explained Ratio 66.53 Component PC635, Cumulative Explained Ratio 66.63 Component PC636, Cumulative Explained Ratio 66.73 Component PC637, Cumulative Explained Ratio 66.82 Component PC638, Cumulative Explained Ratio 66.92 Component PC639, Cumulative Explained Ratio 67.02 Component PC640, Cumulative Explained Ratio 67.12 Component PC641, Cumulative Explained Ratio 67.22 Component PC642, Cumulative Explained Ratio 67.32 Component PC643, Cumulative Explained Ratio 67.41 Component PC644, Cumulative Explained Ratio 67.51 Component PC645, Cumulative Explained Ratio 67.61 Component PC646, Cumulative Explained Ratio 67.71 Component PC647, Cumulative Explained Ratio 67.81 Component PC648, Cumulative Explained Ratio 67.91 Component PC649, Cumulative Explained Ratio 68.0 Component PC650, Cumulative Explained Ratio 68.1 Component PC651, Cumulative Explained Ratio 68.2 Component PC652, Cumulative Explained Ratio 68.3 Component PC653, Cumulative Explained Ratio 68.4 Component PC654, Cumulative Explained Ratio 68.5 Component PC655, Cumulative Explained Ratio 68.59 Component PC656, Cumulative Explained Ratio 68.69 Component PC657, Cumulative Explained Ratio 68.79 Component PC658, Cumulative Explained Ratio 68.89 Component PC659, Cumulative Explained Ratio 68.99 Component PC660, Cumulative Explained Ratio 69.09 Component PC661, Cumulative Explained Ratio 69.18 Component PC662, Cumulative Explained Ratio 69.28 Component PC663, Cumulative Explained Ratio 69.38 Component PC664, Cumulative Explained Ratio 69.48 Component PC665, Cumulative Explained Ratio 69.58 Component PC666, Cumulative Explained Ratio 69.68 Component PC667, Cumulative Explained Ratio 69.77 Component PC668, Cumulative Explained Ratio 69.87 Component PC669, Cumulative Explained Ratio 69.97 Component PC670, Cumulative Explained Ratio 70.07 Component PC671, Cumulative Explained Ratio 70.17 Component PC672, Cumulative Explained Ratio 70.27 Component PC673, Cumulative Explained Ratio 70.36 Component PC674, Cumulative Explained Ratio 70.46 Component PC675, Cumulative Explained Ratio 70.56 Component PC676, Cumulative Explained Ratio 70.66 Component PC677, Cumulative Explained Ratio 70.76 Component PC678, Cumulative Explained Ratio 70.86 Component PC679, Cumulative Explained Ratio 70.95 Component PC680, Cumulative Explained Ratio 71.05 Component PC681, Cumulative Explained Ratio 71.15 Component PC682, Cumulative Explained Ratio 71.25 Component PC683, Cumulative Explained Ratio 71.35 Component PC684, Cumulative Explained Ratio 71.45 Component PC685, Cumulative Explained Ratio 71.54 Component PC686, Cumulative Explained Ratio 71.64 Component PC687, Cumulative Explained Ratio 71.74 Component PC688, Cumulative Explained Ratio 71.84 Component PC689, Cumulative Explained Ratio 71.94 Component PC690, Cumulative Explained Ratio 72.04 Component PC691, Cumulative Explained Ratio 72.13 Component PC692, Cumulative Explained Ratio 72.23 Component PC693, Cumulative Explained Ratio 72.33 Component PC694, Cumulative Explained Ratio 72.43 Component PC695, Cumulative Explained Ratio 72.53 Component PC696, Cumulative Explained Ratio 72.63 Component PC697, Cumulative Explained Ratio 72.72 Component PC698, Cumulative Explained Ratio 72.82 Component PC699, Cumulative Explained Ratio 72.92 Component PC700, Cumulative Explained Ratio 73.02 Component PC701, Cumulative Explained Ratio 73.12 Component PC702, Cumulative Explained Ratio 73.22 Component PC703, Cumulative Explained Ratio 73.31 Component PC704, Cumulative Explained Ratio 73.41 Component PC705, Cumulative Explained Ratio 73.51 Component PC706, Cumulative Explained Ratio 73.61 Component PC707, Cumulative Explained Ratio 73.71 Component PC708, Cumulative Explained Ratio 73.81 Component PC709, Cumulative Explained Ratio 73.9 Component PC710, Cumulative Explained Ratio 74.0 Component PC711, Cumulative Explained Ratio 74.1 Component PC712, Cumulative Explained Ratio 74.2 Component PC713, Cumulative Explained Ratio 74.3 Component PC714, Cumulative Explained Ratio 74.4 Component PC715, Cumulative Explained Ratio 74.49 Component PC716, Cumulative Explained Ratio 74.59 Component PC717, Cumulative Explained Ratio 74.69 Component PC718, Cumulative Explained Ratio 74.79 Component PC719, Cumulative Explained Ratio 74.89 Component PC720, Cumulative Explained Ratio 74.99 Component PC721, Cumulative Explained Ratio 75.08 Component PC722, Cumulative Explained Ratio 75.18 Component PC723, Cumulative Explained Ratio 75.28 Component PC724, Cumulative Explained Ratio 75.38 Component PC725, Cumulative Explained Ratio 75.48 Component PC726, Cumulative Explained Ratio 75.58 Component PC727, Cumulative Explained Ratio 75.67 Component PC728, Cumulative Explained Ratio 75.77 Component PC729, Cumulative Explained Ratio 75.87 Component PC730, Cumulative Explained Ratio 75.97 Component PC731, Cumulative Explained Ratio 76.07 Component PC732, Cumulative Explained Ratio 76.17 Component PC733, Cumulative Explained Ratio 76.26 Component PC734, Cumulative Explained Ratio 76.36 Component PC735, Cumulative Explained Ratio 76.46 Component PC736, Cumulative Explained Ratio 76.56 Component PC737, Cumulative Explained Ratio 76.66 Component PC738, Cumulative Explained Ratio 76.76 Component PC739, Cumulative Explained Ratio 76.85 Component PC740, Cumulative Explained Ratio 76.95 Component PC741, Cumulative Explained Ratio 77.05 Component PC742, Cumulative Explained Ratio 77.15 Component PC743, Cumulative Explained Ratio 77.25 Component PC744, Cumulative Explained Ratio 77.35 Component PC745, Cumulative Explained Ratio 77.44 Component PC746, Cumulative Explained Ratio 77.54 Component PC747, Cumulative Explained Ratio 77.64 Component PC748, Cumulative Explained Ratio 77.74 Component PC749, Cumulative Explained Ratio 77.84 Component PC750, Cumulative Explained Ratio 77.94 Component PC751, Cumulative Explained Ratio 78.03 Component PC752, Cumulative Explained Ratio 78.13 Component PC753, Cumulative Explained Ratio 78.23 Component PC754, Cumulative Explained Ratio 78.33 Component PC755, Cumulative Explained Ratio 78.43 Component PC756, Cumulative Explained Ratio 78.53 Component PC757, Cumulative Explained Ratio 78.62 Component PC758, Cumulative Explained Ratio 78.72 Component PC759, Cumulative Explained Ratio 78.82 Component PC760, Cumulative Explained Ratio 78.92 Component PC761, Cumulative Explained Ratio 79.02 Component PC762, Cumulative Explained Ratio 79.12 Component PC763, Cumulative Explained Ratio 79.21 Component PC764, Cumulative Explained Ratio 79.31 Component PC765, Cumulative Explained Ratio 79.41 Component PC766, Cumulative Explained Ratio 79.51 Component PC767, Cumulative Explained Ratio 79.61 Component PC768, Cumulative Explained Ratio 79.71 Component PC769, Cumulative Explained Ratio 79.8 Component PC770, Cumulative Explained Ratio 79.9 Component PC771, Cumulative Explained Ratio 80.0 Component PC772, Cumulative Explained Ratio 80.1 Component PC773, Cumulative Explained Ratio 80.2 Component PC774, Cumulative Explained Ratio 80.3 Component PC775, Cumulative Explained Ratio 80.39 Component PC776, Cumulative Explained Ratio 80.49 Component PC777, Cumulative Explained Ratio 80.59 Component PC778, Cumulative Explained Ratio 80.69 Component PC779, Cumulative Explained Ratio 80.79 Component PC780, Cumulative Explained Ratio 80.89 Component PC781, Cumulative Explained Ratio 80.98 Component PC782, Cumulative Explained Ratio 81.08 Component PC783, Cumulative Explained Ratio 81.18 Component PC784, Cumulative Explained Ratio 81.28 Component PC785, Cumulative Explained Ratio 81.38 Component PC786, Cumulative Explained Ratio 81.48 Component PC787, Cumulative Explained Ratio 81.57 Component PC788, Cumulative Explained Ratio 81.67 Component PC789, Cumulative Explained Ratio 81.77 Component PC790, Cumulative Explained Ratio 81.87 Component PC791, Cumulative Explained Ratio 81.97 Component PC792, Cumulative Explained Ratio 82.07 Component PC793, Cumulative Explained Ratio 82.17 Component PC794, Cumulative Explained Ratio 82.26 Component PC795, Cumulative Explained Ratio 82.36 Component PC796, Cumulative Explained Ratio 82.46 Component PC797, Cumulative Explained Ratio 82.56 Component PC798, Cumulative Explained Ratio 82.66 Component PC799, Cumulative Explained Ratio 82.76 Component PC800, Cumulative Explained Ratio 82.85 Component PC801, Cumulative Explained Ratio 82.95 Component PC802, Cumulative Explained Ratio 83.05 Component PC803, Cumulative Explained Ratio 83.15 Component PC804, Cumulative Explained Ratio 83.25 Component PC805, Cumulative Explained Ratio 83.35 Component PC806, Cumulative Explained Ratio 83.44 Component PC807, Cumulative Explained Ratio 83.54 Component PC808, Cumulative Explained Ratio 83.64 Component PC809, Cumulative Explained Ratio 83.74 Component PC810, Cumulative Explained Ratio 83.84 Component PC811, Cumulative Explained Ratio 83.94 Component PC812, Cumulative Explained Ratio 84.03 Component PC813, Cumulative Explained Ratio 84.13 Component PC814, Cumulative Explained Ratio 84.23 Component PC815, Cumulative Explained Ratio 84.33 Component PC816, Cumulative Explained Ratio 84.43 Component PC817, Cumulative Explained Ratio 84.53 Component PC818, Cumulative Explained Ratio 84.62 Component PC819, Cumulative Explained Ratio 84.72 Component PC820, Cumulative Explained Ratio 84.82 Component PC821, Cumulative Explained Ratio 84.92 Component PC822, Cumulative Explained Ratio 85.02 Component PC823, Cumulative Explained Ratio 85.12 Component PC824, Cumulative Explained Ratio 85.21 Component PC825, Cumulative Explained Ratio 85.31 Component PC826, Cumulative Explained Ratio 85.41 Component PC827, Cumulative Explained Ratio 85.51 Component PC828, Cumulative Explained Ratio 85.61 Component PC829, Cumulative Explained Ratio 85.71 Component PC830, Cumulative Explained Ratio 85.8 Component PC831, Cumulative Explained Ratio 85.9 Component PC832, Cumulative Explained Ratio 86.0 Component PC833, Cumulative Explained Ratio 86.1 Component PC834, Cumulative Explained Ratio 86.2 Component PC835, Cumulative Explained Ratio 86.3 Component PC836, Cumulative Explained Ratio 86.39 Component PC837, Cumulative Explained Ratio 86.49 Component PC838, Cumulative Explained Ratio 86.59 Component PC839, Cumulative Explained Ratio 86.69 Component PC840, Cumulative Explained Ratio 86.79 Component PC841, Cumulative Explained Ratio 86.89 Component PC842, Cumulative Explained Ratio 86.98 Component PC843, Cumulative Explained Ratio 87.08 Component PC844, Cumulative Explained Ratio 87.18 Component PC845, Cumulative Explained Ratio 87.28 Component PC846, Cumulative Explained Ratio 87.38 Component PC847, Cumulative Explained Ratio 87.48 Component PC848, Cumulative Explained Ratio 87.57 Component PC849, Cumulative Explained Ratio 87.67 Component PC850, Cumulative Explained Ratio 87.77 Component PC851, Cumulative Explained Ratio 87.87 Component PC852, Cumulative Explained Ratio 87.97 Component PC853, Cumulative Explained Ratio 88.07 Component PC854, Cumulative Explained Ratio 88.16 Component PC855, Cumulative Explained Ratio 88.26 Component PC856, Cumulative Explained Ratio 88.36 Component PC857, Cumulative Explained Ratio 88.46 Component PC858, Cumulative Explained Ratio 88.56 Component PC859, Cumulative Explained Ratio 88.66 Component PC860, Cumulative Explained Ratio 88.75 Component PC861, Cumulative Explained Ratio 88.85 Component PC862, Cumulative Explained Ratio 88.95 Component PC863, Cumulative Explained Ratio 89.05 Component PC864, Cumulative Explained Ratio 89.15 Component PC865, Cumulative Explained Ratio 89.25 Component PC866, Cumulative Explained Ratio 89.34 Component PC867, Cumulative Explained Ratio 89.44 Component PC868, Cumulative Explained Ratio 89.54 Component PC869, Cumulative Explained Ratio 89.64 Component PC870, Cumulative Explained Ratio 89.74 Component PC871, Cumulative Explained Ratio 89.84 Component PC872, Cumulative Explained Ratio 89.93 Component PC873, Cumulative Explained Ratio 90.03 Component PC874, Cumulative Explained Ratio 90.13 Component PC875, Cumulative Explained Ratio 90.23 Component PC876, Cumulative Explained Ratio 90.33 Component PC877, Cumulative Explained Ratio 90.43 Component PC878, Cumulative Explained Ratio 90.52 Component PC879, Cumulative Explained Ratio 90.62 Component PC880, Cumulative Explained Ratio 90.72 Component PC881, Cumulative Explained Ratio 90.82 Component PC882, Cumulative Explained Ratio 90.92 Component PC883, Cumulative Explained Ratio 91.02 Component PC884, Cumulative Explained Ratio 91.11 Component PC885, Cumulative Explained Ratio 91.21 Component PC886, Cumulative Explained Ratio 91.31 Component PC887, Cumulative Explained Ratio 91.41 Component PC888, Cumulative Explained Ratio 91.5 Component PC889, Cumulative Explained Ratio 91.6 Component PC890, Cumulative Explained Ratio 91.7 Component PC891, Cumulative Explained Ratio 91.79 Component PC892, Cumulative Explained Ratio 91.89 Component PC893, Cumulative Explained Ratio 91.98 Component PC894, Cumulative Explained Ratio 92.08 Component PC895, Cumulative Explained Ratio 92.17 Component PC896, Cumulative Explained Ratio 92.27 Component PC897, Cumulative Explained Ratio 92.36 Component PC898, Cumulative Explained Ratio 92.46 Component PC899, Cumulative Explained Ratio 92.55 Component PC900, Cumulative Explained Ratio 92.65 Component PC901, Cumulative Explained Ratio 92.74 Component PC902, Cumulative Explained Ratio 92.83 Component PC903, Cumulative Explained Ratio 92.93 Component PC904, Cumulative Explained Ratio 93.02 Component PC905, Cumulative Explained Ratio 93.11 Component PC906, Cumulative Explained Ratio 93.2 Component PC907, Cumulative Explained Ratio 93.3 Component PC908, Cumulative Explained Ratio 93.39 Component PC909, Cumulative Explained Ratio 93.48 Component PC910, Cumulative Explained Ratio 93.57 Component PC911, Cumulative Explained Ratio 93.67 Component PC912, Cumulative Explained Ratio 93.76 Component PC913, Cumulative Explained Ratio 93.85 Component PC914, Cumulative Explained Ratio 93.94 Component PC915, Cumulative Explained Ratio 94.03 Component PC916, Cumulative Explained Ratio 94.13 Component PC917, Cumulative Explained Ratio 94.22 Component PC918, Cumulative Explained Ratio 94.31 Component PC919, Cumulative Explained Ratio 94.4 Component PC920, Cumulative Explained Ratio 94.49 Component PC921, Cumulative Explained Ratio 94.58 Component PC922, Cumulative Explained Ratio 94.67 Component PC923, Cumulative Explained Ratio 94.76 Component PC924, Cumulative Explained Ratio 94.85 Component PC925, Cumulative Explained Ratio 94.94 Component PC926, Cumulative Explained Ratio 95.03 Component PC927, Cumulative Explained Ratio 95.12 Component PC928, Cumulative Explained Ratio 95.21 Component PC929, Cumulative Explained Ratio 95.3 Component PC930, Cumulative Explained Ratio 95.39 Component PC931, Cumulative Explained Ratio 95.48 Component PC932, Cumulative Explained Ratio 95.57 Component PC933, Cumulative Explained Ratio 95.66 Component PC934, Cumulative Explained Ratio 95.75 Component PC935, Cumulative Explained Ratio 95.84 Component PC936, Cumulative Explained Ratio 95.93 Component PC937, Cumulative Explained Ratio 96.02 Component PC938, Cumulative Explained Ratio 96.11 Component PC939, Cumulative Explained Ratio 96.2 Component PC940, Cumulative Explained Ratio 96.28 Component PC941, Cumulative Explained Ratio 96.37 Component PC942, Cumulative Explained Ratio 96.46 Component PC943, Cumulative Explained Ratio 96.55 Component PC944, Cumulative Explained Ratio 96.64 Component PC945, Cumulative Explained Ratio 96.72 Component PC946, Cumulative Explained Ratio 96.81 Component PC947, Cumulative Explained Ratio 96.9 Component PC948, Cumulative Explained Ratio 96.99 Component PC949, Cumulative Explained Ratio 97.08 Component PC950, Cumulative Explained Ratio 97.16 Component PC951, Cumulative Explained Ratio 97.25 Component PC952, Cumulative Explained Ratio 97.34 Component PC953, Cumulative Explained Ratio 97.42 Component PC954, Cumulative Explained Ratio 97.51 Component PC955, Cumulative Explained Ratio 97.6 Component PC956, Cumulative Explained Ratio 97.68 Component PC957, Cumulative Explained Ratio 97.77 Component PC958, Cumulative Explained Ratio 97.85 Component PC959, Cumulative Explained Ratio 97.94 Component PC960, Cumulative Explained Ratio 98.02 Component PC961, Cumulative Explained Ratio 98.11 Component PC962, Cumulative Explained Ratio 98.19 Component PC963, Cumulative Explained Ratio 98.28 Component PC964, Cumulative Explained Ratio 98.36 Component PC965, Cumulative Explained Ratio 98.45 Component PC966, Cumulative Explained Ratio 98.53 Component PC967, Cumulative Explained Ratio 98.61 Component PC968, Cumulative Explained Ratio 98.7 Component PC969, Cumulative Explained Ratio 98.78 Component PC970, Cumulative Explained Ratio 98.86 Component PC971, Cumulative Explained Ratio 98.94 Component PC972, Cumulative Explained Ratio 99.02 Component PC973, Cumulative Explained Ratio 99.1 Component PC974, Cumulative Explained Ratio 99.18 Component PC975, Cumulative Explained Ratio 99.26 Component PC976, Cumulative Explained Ratio 99.33 Component PC977, Cumulative Explained Ratio 99.41 Component PC978, Cumulative Explained Ratio 99.48 Component PC979, Cumulative Explained Ratio 99.55 Component PC980, Cumulative Explained Ratio 99.62 Component PC981, Cumulative Explained Ratio 99.68 Component PC982, Cumulative Explained Ratio 99.74 Component PC983, Cumulative Explained Ratio 99.8 Component PC984, Cumulative Explained Ratio 99.85 Component PC985, Cumulative Explained Ratio 99.89 Component PC986, Cumulative Explained Ratio 99.92 Component PC987, Cumulative Explained Ratio 99.95 Component PC988, Cumulative Explained Ratio 99.97 Component PC989, Cumulative Explained Ratio 99.98 Component PC990, Cumulative Explained Ratio 100.0 Component PC991, Cumulative Explained Ratio 100.0 Component PC992, Cumulative Explained Ratio 100.0 Component PC993, Cumulative Explained Ratio 100.0 Component PC994, Cumulative Explained Ratio 100.0 Component PC995, Cumulative Explained Ratio 100.0 Component PC996, Cumulative Explained Ratio 100.0 Component PC997, Cumulative Explained Ratio 100.0 Component PC998, Cumulative Explained Ratio 100.0 Component PC999, Cumulative Explained Ratio 100.0 Component PC1000, Cumulative Explained Ratio 100.0 Component PC1001, Cumulative Explained Ratio 100.0 Component PC1002, Cumulative Explained Ratio 100.0 Component PC1003, Cumulative Explained Ratio 100.0 Component PC1004, Cumulative Explained Ratio 100.0 Component PC1005, Cumulative Explained Ratio 100.0 Component PC1006, Cumulative Explained Ratio 100.0 Component PC1007, Cumulative Explained Ratio 100.0 Component PC1008, Cumulative Explained Ratio 100.0 List of most relevant features: ['INCOME', 'AGE', 'HPHONE_D', 'N_ODATEDW', 'NUMCHLD', 'CONTROLN', 'TCODE', 'WEALTH1', 'CHILD18_ ', 'PEPSTRFL_ ', 'STATE_CA', 'OSOURCE_MCO', 'OSOURCE_APP', 'OSOURCE_NWN', 'OSOURCE_L16', 'OSOURCE_ENQ', 'OSOURCE_STV', 'OSOURCE_AGS', 'OSOURCE_MAT', 'OSOURCE_PBL', 'OSOURCE_ADD', 'OSOURCE_ALZ', 'OSOURCE_SUN', 'OSOURCE_FOR', 'OSOURCE_GPS', 'OSOURCE_BRY', 'OSOURCE_LKE', 'OSOURCE_PCL', 'OSOURCE_SYC', 'OSOURCE_WRG', 'OSOURCE_WIG', 'OSOURCE_LEO', 'OSOURCE_MON', 'OSOURCE_TVH', 'OSOURCE_HAM', 'OSOURCE_D02', 'OSOURCE_DON', 'OSOURCE_KEN', 'OSOURCE_HOW', 'OSOURCE_STL', 'OSOURCE_MAD', 'OSOURCE_PRV', 'OSOURCE_GUR', 'OSOURCE_TPS', 'OSOURCE_SPG', 'OSOURCE_CAW', 'OSOURCE_COK', 'OSOURCE_ARB', 'OSOURCE_LIF', 'OSOURCE_NSH', 'OSOURCE_BAN', 'OSOURCE_DBL', 'OSOURCE_KNG', 'OSOURCE_NEW', 'OSOURCE_NAD', 'OSOURCE_RED', 'OSOURCE_DDA', 'OSOURCE_TIM', 'OSOURCE_HHL', 'OSOURCE_MB1', 'OSOURCE_TVF', 'OSOURCE_LVT', 'OSOURCE_HHS', 'OSOURCE_HER', 'OSOURCE_AIR', 'OSOURCE_ASE', 'OSOURCE_MIC', 'OSOURCE_TVG', 'OSOURCE_NTW', 'OSOURCE_HFS', 'OSOURCE_PME', 'OSOURCE_AQU', 'OSOURCE_STA', 'OSOURCE_EAS', 'OSOURCE_GDA', 'OSOURCE_ASK', 'OSOURCE_AHC', 'OSOURCE_PGR', 'OSOURCE_NHB', 'OSOURCE_NWF', 'OSOURCE_CSM', 'OSOURCE_GAR', 'OSOURCE_GOD', 'OSOURCE_GRT', 'OSOURCE_JFY', 'OSOURCE_RAY', 'OSOURCE_MWD', 'OSOURCE_BLI', 'OSOURCE_PBK', 'OSOURCE_CNC', 'OSOURCE_MSD', 'OSOURCE_L06', 'OSOURCE_SCP', 'OSOURCE_ROA', 'OSOURCE_MBB', 'OSOURCE_PLU', 'OSOURCE_AKM', 'OSOURCE_ACS', 'OSOURCE_FGM', 'OSOURCE_L03', 'OSOURCE_PSM', 'OSOURCE_NWD', 'OSOURCE_QUI', 'OSOURCE_IDE', 'OSOURCE_MM3', 'OSOURCE_TRN', 'OSOURCE_CHK', 'OSOURCE_BRE', 'OSOURCE_NOR', 'OSOURCE_TV1', 'OSOURCE_SFH', 'OSOURCE_EPL', 'OSOURCE_ADM', 'OSOURCE_MM2', 'OSOURCE_OVS', 'OSOURCE_USS', 'OSOURCE_TYL', 'OSOURCE_SPR', 'OSOURCE_LAK', 'OSOURCE_SMM', 'OSOURCE_GLP', 'OSOURCE_HSP', 'OSOURCE_UBA', 'OSOURCE_WIS', 'OSOURCE_WFD', 'OSOURCE_MM1', 'OSOURCE_COH', 'OSOURCE_QNT', 'OSOURCE_USA', 'OSOURCE_ASS', 'OSOURCE_WMD', 'OSOURCE_JUD', 'OSOURCE_CMT', 'OSOURCE_OLY', 'OSOURCE_DLM', 'OSOURCE_PLN', 'OSOURCE_LEE', 'OSOURCE_WAR', 'OSOURCE_YKD', 'OSOURCE_YKA', 'OSOURCE_TRU', 'OSOURCE_OHI', 'OSOURCE_MIS', 'OSOURCE_FAR', 'OSOURCE_DNB', 'OSOURCE_NPP', 'OSOURCE_TRO', 'OSOURCE_FIG', 'OSOURCE_WLW', 'OSOURCE_FLD', 'OSOURCE_SUF', 'OSOURCE_LPN', 'OSOURCE_KUR', 'OSOURCE_NSN', 'OSOURCE_NFB', 'OSOURCE_DRH', 'OSOURCE_REF', 'OSOURCE_KIP', 'OSOURCE_DOW', 'OSOURCE_RPC', 'OSOURCE_EPS', 'OSOURCE_ASH', 'OSOURCE_DHR', 'OSOURCE_ANN', 'OSOURCE_GHS', 'OSOURCE_DNL', 'OSOURCE_AMH', 'OSOURCE_ALD', 'OSOURCE_GPD', 'OSOURCE_SEP', 'OSOURCE_MYO', 'OSOURCE_ABC', 'OSOURCE_ACT', 'OSOURCE_RKB', 'OSOURCE_BRK', 'OSOURCE_MIL', 'OSOURCE_VIG', 'OSOURCE_MDC', 'OSOURCE_OLD', 'OSOURCE_MER', 'OSOURCE_HIL', 'OSOURCE_STK', 'OSOURCE_AR1', 'OSOURCE_TMX', 'OSOURCE_AMU', 'OSOURCE_TWM', 'OSOURCE_ARC', 'OSOURCE_FOS', 'OSOURCE_MTR', 'OSOURCE_ADR', 'OSOURCE_SMI', 'OSOURCE_VTM', 'OSOURCE_WAL', 'OSOURCE_AHN', 'OSOURCE_HEA', 'OSOURCE_DBT', 'OSOURCE_NEX', 'OSOURCE_TRA', 'OSOURCE_OD2', 'OSOURCE_NSM', 'OSOURCE_PHR', 'OSOURCE_NYL', 'OSOURCE_AAD', 'OSOURCE_TLB', 'OSOURCE_CRE', 'OSOURCE_AIC', 'OSOURCE_GCP', 'OSOURCE_HMP', 'OSOURCE_MAY', 'OSOURCE_SSL', 'OSOURCE_HHV', 'OSOURCE_OD1', 'OSOURCE_HHC', 'OSOURCE_DTM', 'OSOURCE_SHL', 'OSOURCE_SMC', 'OSOURCE_EQM', 'OSOURCE_MWA', 'OSOURCE_LOB', 'OSOURCE_NAP', 'OSOURCE_VBK', 'OSOURCE_SMS', 'OSOURCE_BHL', 'OSOURCE_SSC', 'OSOURCE_JCD', 'OSOURCE_SUM', 'OSOURCE_EP1', 'OSOURCE_THM', 'OSOURCE_TAS', 'OSOURCE_STJ', 'OSOURCE_USN', 'OSOURCE_EPI', 'OSOURCE_DTR', 'OSOURCE_MLF', 'OSOURCE_L0L', 'OSOURCE_ACB', 'OSOURCE_ATL', 'OSOURCE_MOP', 'OSOURCE_CUL', 'OSOURCE_HUT', 'OSOURCE_CYB', 'OSOURCE_DBD', 'OSOURCE_NWL', 'OSOURCE_TOG', 'OSOURCE_MHM', 'OSOURCE_ORG', 'OSOURCE_INM', 'OSOURCE_NSL', 'OSOURCE_OXM', 'OSOURCE_VFW', 'OSOURCE_NES', 'OSOURCE_GBK', 'OSOURCE_SEL', 'OSOURCE_CRS', 'OSOURCE_WBY', 'OSOURCE_PWR', 'OSOURCE_CHI', 'OSOURCE_PCC', 'OSOURCE_CCP', 'OSOURCE_L14', 'OSOURCE_MBL', 'OSOURCE_AVS', 'OSOURCE_LIL', 'OSOURCE_AP1', 'OSOURCE_HCK', 'OSOURCE_ALS', 'OSOURCE_BML', 'OSOURCE_TOD', 'OSOURCE_YAN', 'OSOURCE_BMG', 'OSOURCE_JLR', 'OSOURCE_MST', 'OSOURCE_BEE', 'OSOURCE_AQK', 'OSOURCE_AHM', 'OSOURCE_HRM', 'OSOURCE_BED', 'OSOURCE_MBT', 'OSOURCE_DRL', 'OSOURCE_FLM', 'OSOURCE_ACC', 'OSOURCE_REG', 'OSOURCE_STE', 'OSOURCE_WOR', 'OSOURCE_AHL', 'OSOURCE_YNF', 'OSOURCE_THE', 'OSOURCE_CGK', 'OSOURCE_HTG', 'OSOURCE_SCL', 'OSOURCE_DLG', 'OSOURCE_IDM', 'OSOURCE_MGU', 'OSOURCE_TRL', 'OSOURCE_L07', 'OSOURCE_RLT', 'OSOURCE_SLF', 'OSOURCE_WND', 'OSOURCE_POW', 'OSOURCE_HLN', 'OSOURCE_SWI', 'OSOURCE_NAM', 'OSOURCE_ARM', 'OSOURCE_ATS', 'OSOURCE_NON', 'OSOURCE_HAC', 'OSOURCE_CBL', 'OSOURCE_WWM', 'OSOURCE_SYZ', 'OSOURCE_L13', 'OSOURCE_IML', 'OSOURCE_CRN', 'OSOURCE_SRN', 'OSOURCE_ASD', 'OSOURCE_CKD', 'OSOURCE_DCK', 'OSOURCE_CPL', 'OSOURCE_BFD', 'OSOURCE_EMI', 'OSOURCE_RNM', 'OSOURCE_MCF', 'OSOURCE_ECK', 'OSOURCE_MV2', 'OSOURCE_CNA', 'OSOURCE_GDM', 'OSOURCE_AHS', 'OSOURCE_HLQ', 'OSOURCE_DSN', 'OSOURCE_STP', 'OSOURCE_JNC', 'OSOURCE_HLA', 'OSOURCE_MWC', 'OSOURCE_MPL', 'OSOURCE_KCP', 'OSOURCE_CAT', 'OSOURCE_RHM', 'OSOURCE_RSM', 'OSOURCE_POI', 'OSOURCE_AMZ', 'OSOURCE_PAR', 'OSOURCE_SUR', 'OSOURCE_HSF', 'OSOURCE_NHR', 'OSOURCE_HOR', 'OSOURCE_VDB', 'OSOURCE_NYH', 'OSOURCE_CSP', 'OSOURCE_DAT', 'OSOURCE_SCO', 'OSOURCE_CTY', 'OSOURCE_BEA', 'OSOURCE_GLD', 'OSOURCE_WWF', 'OSOURCE_ACG', 'OSOURCE_SSM', 'OSOURCE_UNV', 'OSOURCE_LEI', 'OSOURCE_ALF', 'OSOURCE_DLL', 'OSOURCE_SPC', 'OSOURCE_CMM', 'OSOURCE_LRD', 'OSOURCE_FHN', 'OSOURCE_OHS', 'OSOURCE_SWP', 'OSOURCE_L09', 'OSOURCE_FDP', 'OSOURCE_ACP', 'OSOURCE_MC1', 'OSOURCE_PHO', 'OSOURCE_DAC', 'OSOURCE_PAL', 'OSOURCE_CYR', 'OSOURCE_MFL', 'OSOURCE_L0C', 'OSOURCE_SH3', 'OSOURCE_GAD', 'OSOURCE_GDF', 'OSOURCE_NWP', 'OSOURCE_PUB', 'OSOURCE_ENC', 'OSOURCE_CRM', 'OSOURCE_RVP', 'OSOURCE_HSC', 'OSOURCE_PEN', 'OSOURCE_PBW', 'OSOURCE_PBC', 'OSOURCE_NPA', 'OSOURCE_FWF', 'OSOURCE_SFL', 'OSOURCE_HPS', 'OSOURCE_MLK', 'OSOURCE_MSH', 'OSOURCE_NNS', 'OSOURCE_LST', 'OSOURCE_NCE', 'OSOURCE_BMS', 'OSOURCE_DIA', 'OSOURCE_COP', 'OSOURCE_SHK', 'OSOURCE_LAN', 'OSOURCE_PTS', 'OSOURCE_WTW', 'OSOURCE_KIT', 'OSOURCE_ENT', 'OSOURCE_DMI', 'OSOURCE_HFH', 'OSOURCE_NUM', 'OSOURCE_SOP', 'OSOURCE_WIL', 'OSOURCE_CJR', 'OSOURCE_L17', 'OSOURCE_BSM', 'OSOURCE_AFP', 'OSOURCE_WER', 'OSOURCE_FST', 'OSOURCE_LRS', 'OSOURCE_TVM', 'OSOURCE_ROM', 'OSOURCE_KTB', 'OSOURCE_SHU', 'OSOURCE_DUN', 'OSOURCE_ORT', 'OSOURCE_SFW', 'OSOURCE_PPL', 'OSOURCE_AWK', 'OSOURCE_CSD', 'OSOURCE_VGL', 'OSOURCE_STY', 'OSOURCE_SH1', 'OSOURCE_HMM', 'OSOURCE_PNY', 'OSOURCE_L24', 'OSOURCE_ACR', 'OSOURCE_MV1', 'OSOURCE_GLN', 'OSOURCE_BRP', 'OSOURCE_L20', 'OSOURCE_HHA', 'OSOURCE_TRE', 'OSOURCE_TCW', 'OSOURCE_MIQ', 'OSOURCE_MLJ', 'OSOURCE_SOC', 'OSOURCE_PSC', 'OSOURCE_SST', 'OSOURCE_INN', 'OSOURCE_RDM', 'OSOURCE_NGR', 'OSOURCE_DAY', 'OSOURCE_POP', 'OSOURCE_SCA', 'OSOURCE_RCW', 'OSOURCE_WDH', 'OSOURCE_SNR', 'OSOURCE_HST', 'OSOURCE_AMJ', 'OSOURCE_GEN', 'OSOURCE_CSC', 'OSOURCE_CFF', 'OSOURCE_MNT', 'OSOURCE_LE2', 'OSOURCE_PGA', 'OSOURCE_TWN', 'OSOURCE_JRV', 'OSOURCE_CMB', 'OSOURCE_CIR', 'OSOURCE_AHB', 'OSOURCE_BLV', 'OSOURCE_LWN', 'OSOURCE_CON', 'OSOURCE_SHE', 'OSOURCE_ABD', 'OSOURCE_DEF', 'OSOURCE_BBT', 'OSOURCE_CHM', 'OSOURCE_SDP', 'OSOURCE_AVD', 'OSOURCE_NHP', 'OSOURCE_VSH', 'OSOURCE_LEM', 'OSOURCE_RCH', 'OSOURCE_BKS', 'OSOURCE_NG2', 'OSOURCE_TFS', 'OSOURCE_CAM', 'OSOURCE_PAT', 'OSOURCE_CRF', 'OSOURCE_GFM', 'OSOURCE_ICK', 'OSOURCE_ISC', 'OSOURCE_CRH', 'OSOURCE_GSP', 'OSOURCE_SUP', 'OSOURCE_WDY', 'OSOURCE_HNZ', 'OSOURCE_ABP', 'OSOURCE_FRM', 'OSOURCE_HCT', 'OSOURCE_AMR', 'OSOURCE_NUR', 'OSOURCE_FII', 'OSOURCE_NPW', 'OSOURCE_HOL', 'OSOURCE_CCB', 'OSOURCE_GNC', 'OSOURCE_PRO', 'OSOURCE_AUD', 'OSOURCE_PCH', 'OSOURCE_SIM', 'OSOURCE_LA2', 'OSOURCE_MCN', 'OSOURCE_AAA', 'OSOURCE_CAB', 'OSOURCE_SJS', 'OSOURCE_BBU', 'OSOURCE_BSH', 'OSOURCE_SDF', 'OSOURCE_POS', 'OSOURCE_IMC', 'OSOURCE_NSA', 'OSOURCE_HEL', 'OSOURCE_CJL', 'OSOURCE_MET', 'OSOURCE_LUK', 'OSOURCE_EAL', 'OSOURCE_PUR', 'OSOURCE_PPM', 'OSOURCE_LSH', 'OSOURCE_CVO', 'OSOURCE_FNC', 'OSOURCE_BTC', 'OSOURCE_HHB', 'OSOURCE_PER', 'OSOURCE_CHB', 'OSOURCE_INT', 'OSOURCE_WKC', 'OSOURCE_HTL', 'OSOURCE_DEC', 'OSOURCE_RBA', 'OSOURCE_BYB', 'OSOURCE_PBY', 'OSOURCE_VCS', 'OSOURCE_USO', 'OSOURCE_SPM', 'OSOURCE_NDL', 'OSOURCE_BIR', 'OSOURCE_BHW', 'OSOURCE_HPR', 'OSOURCE_JTA', 'OSOURCE_QEC', 'OSOURCE_IAP', 'OSOURCE_AMT', 'OSOURCE_NCC', 'OSOURCE_ELL', 'OSOURCE_BHB', 'OSOURCE_DAN', 'OSOURCE_BOS', 'OSOURCE_BRC', 'OSOURCE_FIF', 'OSOURCE_CDC', 'OSOURCE_TVP', 'OSOURCE_NG1', 'OSOURCE_SEQ', 'OSOURCE_AMG', 'OSOURCE_EXS', 'OSOURCE_JTB', 'OSOURCE_BUY', 'OSOURCE_ADA', 'OSOURCE_CIL', 'OSOURCE_CGS', 'OSOURCE_MGA', 'OSOURCE_MTS', 'OSOURCE_DWC', 'OSOURCE_SAL', 'OSOURCE_NPL', 'OSOURCE_PRE', 'OSOURCE_IHS', 'OSOURCE_ZOY', 'OSOURCE_BDG', 'OSOURCE_MGV', 'OSOURCE_RRR', 'OSOURCE_CHR', 'OSOURCE_SPH', 'OSOURCE_IAW', 'OSOURCE_FRA', 'OSOURCE_WRK', 'OSOURCE_D01', 'OSOURCE_SAZ', 'OSOURCE_TMS', 'OSOURCE_AME', 'OSOURCE_SH2', 'OSOURCE_WCP', 'OSOURCE_CMP', 'OSOURCE_CNL', 'OSOURCE_BYL', 'OSOURCE_OWN', 'OSOURCE_FHL', 'OSOURCE_SEW', 'OSOURCE_SEX', 'OSOURCE_ACL', 'OSOURCE_BET', 'OSOURCE_WRT', 'OSOURCE_FNH', 'OSOURCE_ISL', 'OSOURCE_ASB', 'OSOURCE_CCS', 'OSOURCE_SCU', 'OSOURCE_LA1', 'OSOURCE_JHO', 'OSOURCE_FLA', 'OSOURCE_BTR', 'OSOURCE_SWM'] Group: DONOR INTERESTS Component PC0, Cumulative Explained Ratio 26.31 Component PC1, Cumulative Explained Ratio 33.93 Component PC2, Cumulative Explained Ratio 39.21 Component PC3, Cumulative Explained Ratio 44.11 Component PC4, Cumulative Explained Ratio 48.91 Component PC5, Cumulative Explained Ratio 53.15 Component PC6, Cumulative Explained Ratio 57.34 Component PC7, Cumulative Explained Ratio 61.48 Component PC8, Cumulative Explained Ratio 65.37 Component PC9, Cumulative Explained Ratio 69.06 Component PC10, Cumulative Explained Ratio 72.56 Component PC11, Cumulative Explained Ratio 76.01 Component PC12, Cumulative Explained Ratio 79.3 Component PC13, Cumulative Explained Ratio 82.55 Component PC14, Cumulative Explained Ratio 85.56 Component PC15, Cumulative Explained Ratio 88.46 Component PC16, Cumulative Explained Ratio 91.28 Component PC17, Cumulative Explained Ratio 93.97 Component PC18, Cumulative Explained Ratio 96.49 Component PC19, Cumulative Explained Ratio 98.58 Component PC20, Cumulative Explained Ratio 100.0 Component PC21, Cumulative Explained Ratio 100.0 Component PC22, Cumulative Explained Ratio 100.0 Component PC23, Cumulative Explained Ratio 100.0 Component PC24, Cumulative Explained Ratio 100.0 Component PC25, Cumulative Explained Ratio 100.0 Component PC26, Cumulative Explained Ratio 100.0 Component PC27, Cumulative Explained Ratio 100.0 Component PC28, Cumulative Explained Ratio 100.0 Component PC29, Cumulative Explained Ratio 100.0 Component PC30, Cumulative Explained Ratio 100.0 Component PC31, Cumulative Explained Ratio 100.0 Component PC32, Cumulative Explained Ratio 100.0 Component PC33, Cumulative Explained Ratio 100.0 Component PC34, Cumulative Explained Ratio 100.0 Component PC35, Cumulative Explained Ratio 100.0 Component PC36, Cumulative Explained Ratio 100.0 Component PC37, Cumulative Explained Ratio 100.0 Component PC38, Cumulative Explained Ratio 100.0 Component PC39, Cumulative Explained Ratio 100.0 List of most relevant features: ['PETS_ ', 'CARDS_Y', 'CARDS_ ', 'PCOWNERS_ ', 'PCOWNERS_Y', 'BOATS_Y', 'BOATS_ ', 'LIFESRC_3', 'COLLECT1_Y', 'HOMEE_Y', 'HOMEE_ ', 'KIDSTUFF_ ', 'KIDSTUFF_Y', 'PHOTO_ ', 'PHOTO_Y', 'CRAFTS_ ', 'CRAFTS_Y', 'CATLG_ ', 'CATLG_Y', 'WALKER_ ', 'WALKER_Y'] Group: OVERLAY DATA Component PC0, Cumulative Explained Ratio 8.02 Component PC1, Cumulative Explained Ratio 15.07 Component PC2, Cumulative Explained Ratio 21.06 Component PC3, Cumulative Explained Ratio 25.99 Component PC4, Cumulative Explained Ratio 30.18 Component PC5, Cumulative Explained Ratio 34.21 Component PC6, Cumulative Explained Ratio 38.06 Component PC7, Cumulative Explained Ratio 41.62 Component PC8, Cumulative Explained Ratio 45.02 Component PC9, Cumulative Explained Ratio 48.36 Component PC10, Cumulative Explained Ratio 51.66 Component PC11, Cumulative Explained Ratio 54.95 Component PC12, Cumulative Explained Ratio 58.15 Component PC13, Cumulative Explained Ratio 61.34 Component PC14, Cumulative Explained Ratio 64.51 Component PC15, Cumulative Explained Ratio 67.67 Component PC16, Cumulative Explained Ratio 70.81 Component PC17, Cumulative Explained Ratio 73.92 Component PC18, Cumulative Explained Ratio 77.02 Component PC19, Cumulative Explained Ratio 80.1 Component PC20, Cumulative Explained Ratio 83.11 Component PC21, Cumulative Explained Ratio 86.1 Component PC22, Cumulative Explained Ratio 89.03 Component PC23, Cumulative Explained Ratio 91.79 Component PC24, Cumulative Explained Ratio 94.44 Component PC25, Cumulative Explained Ratio 96.67 Component PC26, Cumulative Explained Ratio 98.53 Component PC27, Cumulative Explained Ratio 100.0 Component PC28, Cumulative Explained Ratio 100.0 Component PC29, Cumulative Explained Ratio 100.0 Component PC30, Cumulative Explained Ratio 100.0 Component PC31, Cumulative Explained Ratio 100.0 Component PC32, Cumulative Explained Ratio 100.0 List of most relevant features: ['FEDGOV', 'VIETVETS', 'MALEVET', 'WWIIVETS', 'WEALTH2', 'GEOCODE_ ', 'MALEMILI', 'STATEGOV', 'LOCALGOV'] Group: PROMOTION HISTORY Component PC0, Cumulative Explained Ratio 1.68 Component PC1, Cumulative Explained Ratio 2.51 Component PC2, Cumulative Explained Ratio 3.28 Component PC3, Cumulative Explained Ratio 4.01 Component PC4, Cumulative Explained Ratio 4.68 Component PC5, Cumulative Explained Ratio 5.3 Component PC6, Cumulative Explained Ratio 5.89 Component PC7, Cumulative Explained Ratio 6.45 Component PC8, Cumulative Explained Ratio 6.97 Component PC9, Cumulative Explained Ratio 7.44 Component PC10, Cumulative Explained Ratio 7.91 Component PC11, Cumulative Explained Ratio 8.37 Component PC12, Cumulative Explained Ratio 8.82 Component PC13, Cumulative Explained Ratio 9.25 Component PC14, Cumulative Explained Ratio 9.68 Component PC15, Cumulative Explained Ratio 10.1 Component PC16, Cumulative Explained Ratio 10.51 Component PC17, Cumulative Explained Ratio 10.92 Component PC18, Cumulative Explained Ratio 11.33 Component PC19, Cumulative Explained Ratio 11.73 Component PC20, Cumulative Explained Ratio 12.11 Component PC21, Cumulative Explained Ratio 12.49 Component PC22, Cumulative Explained Ratio 12.86 Component PC23, Cumulative Explained Ratio 13.23 Component PC24, Cumulative Explained Ratio 13.58 Component PC25, Cumulative Explained Ratio 13.93 Component PC26, Cumulative Explained Ratio 14.28 Component PC27, Cumulative Explained Ratio 14.63 Component PC28, Cumulative Explained Ratio 14.96 Component PC29, Cumulative Explained Ratio 15.29 Component PC30, Cumulative Explained Ratio 15.63 Component PC31, Cumulative Explained Ratio 15.95 Component PC32, Cumulative Explained Ratio 16.28 Component PC33, Cumulative Explained Ratio 16.59 Component PC34, Cumulative Explained Ratio 16.91 Component PC35, Cumulative Explained Ratio 17.22 Component PC36, Cumulative Explained Ratio 17.54 Component PC37, Cumulative Explained Ratio 17.84 Component PC38, Cumulative Explained Ratio 18.15 Component PC39, Cumulative Explained Ratio 18.45 Component PC40, Cumulative Explained Ratio 18.75 Component PC41, Cumulative Explained Ratio 19.04 Component PC42, Cumulative Explained Ratio 19.34 Component PC43, Cumulative Explained Ratio 19.63 Component PC44, Cumulative Explained Ratio 19.91 Component PC45, Cumulative Explained Ratio 20.2 Component PC46, Cumulative Explained Ratio 20.48 Component PC47, Cumulative Explained Ratio 20.76 Component PC48, Cumulative Explained Ratio 21.04 Component PC49, Cumulative Explained Ratio 21.32 Component PC50, Cumulative Explained Ratio 21.59 Component PC51, Cumulative Explained Ratio 21.87 Component PC52, Cumulative Explained Ratio 22.13 Component PC53, Cumulative Explained Ratio 22.4 Component PC54, Cumulative Explained Ratio 22.67 Component PC55, Cumulative Explained Ratio 22.93 Component PC56, Cumulative Explained Ratio 23.19 Component PC57, Cumulative Explained Ratio 23.45 Component PC58, Cumulative Explained Ratio 23.71 Component PC59, Cumulative Explained Ratio 23.97 Component PC60, Cumulative Explained Ratio 24.22 Component PC61, Cumulative Explained Ratio 24.48 Component PC62, Cumulative Explained Ratio 24.73 Component PC63, Cumulative Explained Ratio 24.98 Component PC64, Cumulative Explained Ratio 25.23 Component PC65, Cumulative Explained Ratio 25.47 Component PC66, Cumulative Explained Ratio 25.72 Component PC67, Cumulative Explained Ratio 25.97 Component PC68, Cumulative Explained Ratio 26.21 Component PC69, Cumulative Explained Ratio 26.45 Component PC70, Cumulative Explained Ratio 26.69 Component PC71, Cumulative Explained Ratio 26.93 Component PC72, Cumulative Explained Ratio 27.17 Component PC73, Cumulative Explained Ratio 27.41 Component PC74, Cumulative Explained Ratio 27.65 Component PC75, Cumulative Explained Ratio 27.88 Component PC76, Cumulative Explained Ratio 28.12 Component PC77, Cumulative Explained Ratio 28.35 Component PC78, Cumulative Explained Ratio 28.58 Component PC79, Cumulative Explained Ratio 28.81 Component PC80, Cumulative Explained Ratio 29.04 Component PC81, Cumulative Explained Ratio 29.27 Component PC82, Cumulative Explained Ratio 29.49 Component PC83, Cumulative Explained Ratio 29.72 Component PC84, Cumulative Explained Ratio 29.94 Component PC85, Cumulative Explained Ratio 30.16 Component PC86, Cumulative Explained Ratio 30.39 Component PC87, Cumulative Explained Ratio 30.61 Component PC88, Cumulative Explained Ratio 30.83 Component PC89, Cumulative Explained Ratio 31.04 Component PC90, Cumulative Explained Ratio 31.26 Component PC91, Cumulative Explained Ratio 31.48 Component PC92, Cumulative Explained Ratio 31.7 Component PC93, Cumulative Explained Ratio 31.91 Component PC94, Cumulative Explained Ratio 32.13 Component PC95, Cumulative Explained Ratio 32.34 Component PC96, Cumulative Explained Ratio 32.55 Component PC97, Cumulative Explained Ratio 32.76 Component PC98, Cumulative Explained Ratio 32.98 Component PC99, Cumulative Explained Ratio 33.18 Component PC100, Cumulative Explained Ratio 33.39 Component PC101, Cumulative Explained Ratio 33.6 Component PC102, Cumulative Explained Ratio 33.81 Component PC103, Cumulative Explained Ratio 34.02 Component PC104, Cumulative Explained Ratio 34.22 Component PC105, Cumulative Explained Ratio 34.43 Component PC106, Cumulative Explained Ratio 34.63 Component PC107, Cumulative Explained Ratio 34.83 Component PC108, Cumulative Explained Ratio 35.03 Component PC109, Cumulative Explained Ratio 35.23 Component PC110, Cumulative Explained Ratio 35.43 Component PC111, Cumulative Explained Ratio 35.63 Component PC112, Cumulative Explained Ratio 35.83 Component PC113, Cumulative Explained Ratio 36.02 Component PC114, Cumulative Explained Ratio 36.22 Component PC115, Cumulative Explained Ratio 36.41 Component PC116, Cumulative Explained Ratio 36.6 Component PC117, Cumulative Explained Ratio 36.8 Component PC118, Cumulative Explained Ratio 36.99 Component PC119, Cumulative Explained Ratio 37.18 Component PC120, Cumulative Explained Ratio 37.37 Component PC121, Cumulative Explained Ratio 37.56 Component PC122, Cumulative Explained Ratio 37.75 Component PC123, Cumulative Explained Ratio 37.94 Component PC124, Cumulative Explained Ratio 38.12 Component PC125, Cumulative Explained Ratio 38.31 Component PC126, Cumulative Explained Ratio 38.49 Component PC127, Cumulative Explained Ratio 38.68 Component PC128, Cumulative Explained Ratio 38.87 Component PC129, Cumulative Explained Ratio 39.05 Component PC130, Cumulative Explained Ratio 39.23 Component PC131, Cumulative Explained Ratio 39.41 Component PC132, Cumulative Explained Ratio 39.6 Component PC133, Cumulative Explained Ratio 39.78 Component PC134, Cumulative Explained Ratio 39.96 Component PC135, Cumulative Explained Ratio 40.14 Component PC136, Cumulative Explained Ratio 40.31 Component PC137, Cumulative Explained Ratio 40.49 Component PC138, Cumulative Explained Ratio 40.67 Component PC139, Cumulative Explained Ratio 40.84 Component PC140, Cumulative Explained Ratio 41.02 Component PC141, Cumulative Explained Ratio 41.19 Component PC142, Cumulative Explained Ratio 41.37 Component PC143, Cumulative Explained Ratio 41.54 Component PC144, Cumulative Explained Ratio 41.72 Component PC145, Cumulative Explained Ratio 41.89 Component PC146, Cumulative Explained Ratio 42.06 Component PC147, Cumulative Explained Ratio 42.23 Component PC148, Cumulative Explained Ratio 42.4 Component PC149, Cumulative Explained Ratio 42.57 Component PC150, Cumulative Explained Ratio 42.74 Component PC151, Cumulative Explained Ratio 42.91 Component PC152, Cumulative Explained Ratio 43.08 Component PC153, Cumulative Explained Ratio 43.25 Component PC154, Cumulative Explained Ratio 43.41 Component PC155, Cumulative Explained Ratio 43.58 Component PC156, Cumulative Explained Ratio 43.74 Component PC157, Cumulative Explained Ratio 43.9 Component PC158, Cumulative Explained Ratio 44.07 Component PC159, Cumulative Explained Ratio 44.23 Component PC160, Cumulative Explained Ratio 44.39 Component PC161, Cumulative Explained Ratio 44.55 Component PC162, Cumulative Explained Ratio 44.7 Component PC163, Cumulative Explained Ratio 44.86 Component PC164, Cumulative Explained Ratio 45.02 Component PC165, Cumulative Explained Ratio 45.17 Component PC166, Cumulative Explained Ratio 45.32 Component PC167, Cumulative Explained Ratio 45.48 Component PC168, Cumulative Explained Ratio 45.63 Component PC169, Cumulative Explained Ratio 45.78 Component PC170, Cumulative Explained Ratio 45.93 Component PC171, Cumulative Explained Ratio 46.08 Component PC172, Cumulative Explained Ratio 46.23 Component PC173, Cumulative Explained Ratio 46.38 Component PC174, Cumulative Explained Ratio 46.53 Component PC175, Cumulative Explained Ratio 46.67 Component PC176, Cumulative Explained Ratio 46.82 Component PC177, Cumulative Explained Ratio 46.96 Component PC178, Cumulative Explained Ratio 47.11 Component PC179, Cumulative Explained Ratio 47.25 Component PC180, Cumulative Explained Ratio 47.4 Component PC181, Cumulative Explained Ratio 47.54 Component PC182, Cumulative Explained Ratio 47.68 Component PC183, Cumulative Explained Ratio 47.82 Component PC184, Cumulative Explained Ratio 47.96 Component PC185, Cumulative Explained Ratio 48.1 Component PC186, Cumulative Explained Ratio 48.23 Component PC187, Cumulative Explained Ratio 48.37 Component PC188, Cumulative Explained Ratio 48.51 Component PC189, Cumulative Explained Ratio 48.64 Component PC190, Cumulative Explained Ratio 48.78 Component PC191, Cumulative Explained Ratio 48.91 Component PC192, Cumulative Explained Ratio 49.05 Component PC193, Cumulative Explained Ratio 49.18 Component PC194, Cumulative Explained Ratio 49.31 Component PC195, Cumulative Explained Ratio 49.45 Component PC196, Cumulative Explained Ratio 49.58 Component PC197, Cumulative Explained Ratio 49.71 Component PC198, Cumulative Explained Ratio 49.84 Component PC199, Cumulative Explained Ratio 49.97 Component PC200, Cumulative Explained Ratio 50.1 Component PC201, Cumulative Explained Ratio 50.23 Component PC202, Cumulative Explained Ratio 50.36 Component PC203, Cumulative Explained Ratio 50.48 Component PC204, Cumulative Explained Ratio 50.61 Component PC205, Cumulative Explained Ratio 50.74 Component PC206, Cumulative Explained Ratio 50.86 Component PC207, Cumulative Explained Ratio 50.99 Component PC208, Cumulative Explained Ratio 51.11 Component PC209, Cumulative Explained Ratio 51.23 Component PC210, Cumulative Explained Ratio 51.36 Component PC211, Cumulative Explained Ratio 51.48 Component PC212, Cumulative Explained Ratio 51.6 Component PC213, Cumulative Explained Ratio 51.72 Component PC214, Cumulative Explained Ratio 51.84 Component PC215, Cumulative Explained Ratio 51.96 Component PC216, Cumulative Explained Ratio 52.08 Component PC217, Cumulative Explained Ratio 52.2 Component PC218, Cumulative Explained Ratio 52.32 Component PC219, Cumulative Explained Ratio 52.43 Component PC220, Cumulative Explained Ratio 52.55 Component PC221, Cumulative Explained Ratio 52.66 Component PC222, Cumulative Explained Ratio 52.78 Component PC223, Cumulative Explained Ratio 52.89 Component PC224, Cumulative Explained Ratio 53.01 Component PC225, Cumulative Explained Ratio 53.12 Component PC226, Cumulative Explained Ratio 53.23 Component PC227, Cumulative Explained Ratio 53.34 Component PC228, Cumulative Explained Ratio 53.46 Component PC229, Cumulative Explained Ratio 53.57 Component PC230, Cumulative Explained Ratio 53.68 Component PC231, Cumulative Explained Ratio 53.79 Component PC232, Cumulative Explained Ratio 53.9 Component PC233, Cumulative Explained Ratio 54.01 Component PC234, Cumulative Explained Ratio 54.11 Component PC235, Cumulative Explained Ratio 54.22 Component PC236, Cumulative Explained Ratio 54.33 Component PC237, Cumulative Explained Ratio 54.44 Component PC238, Cumulative Explained Ratio 54.55 Component PC239, Cumulative Explained Ratio 54.65 Component PC240, Cumulative Explained Ratio 54.76 Component PC241, Cumulative Explained Ratio 54.87 Component PC242, Cumulative Explained Ratio 54.97 Component PC243, Cumulative Explained Ratio 55.08 Component PC244, Cumulative Explained Ratio 55.18 Component PC245, Cumulative Explained Ratio 55.29 Component PC246, Cumulative Explained Ratio 55.39 Component PC247, Cumulative Explained Ratio 55.5 Component PC248, Cumulative Explained Ratio 55.6 Component PC249, Cumulative Explained Ratio 55.7 Component PC250, Cumulative Explained Ratio 55.81 Component PC251, Cumulative Explained Ratio 55.91 Component PC252, Cumulative Explained Ratio 56.01 Component PC253, Cumulative Explained Ratio 56.11 Component PC254, Cumulative Explained Ratio 56.22 Component PC255, Cumulative Explained Ratio 56.32 Component PC256, Cumulative Explained Ratio 56.42 Component PC257, Cumulative Explained Ratio 56.52 Component PC258, Cumulative Explained Ratio 56.62 Component PC259, Cumulative Explained Ratio 56.72 Component PC260, Cumulative Explained Ratio 56.82 Component PC261, Cumulative Explained Ratio 56.92 Component PC262, Cumulative Explained Ratio 57.02 Component PC263, Cumulative Explained Ratio 57.12 Component PC264, Cumulative Explained Ratio 57.22 Component PC265, Cumulative Explained Ratio 57.31 Component PC266, Cumulative Explained Ratio 57.41 Component PC267, Cumulative Explained Ratio 57.51 Component PC268, Cumulative Explained Ratio 57.61 Component PC269, Cumulative Explained Ratio 57.71 Component PC270, Cumulative Explained Ratio 57.8 Component PC271, Cumulative Explained Ratio 57.9 Component PC272, Cumulative Explained Ratio 58.0 Component PC273, Cumulative Explained Ratio 58.09 Component PC274, Cumulative Explained Ratio 58.19 Component PC275, Cumulative Explained Ratio 58.28 Component PC276, Cumulative Explained Ratio 58.38 Component PC277, Cumulative Explained Ratio 58.47 Component PC278, Cumulative Explained Ratio 58.57 Component PC279, Cumulative Explained Ratio 58.66 Component PC280, Cumulative Explained Ratio 58.76 Component PC281, Cumulative Explained Ratio 58.85 Component PC282, Cumulative Explained Ratio 58.94 Component PC283, Cumulative Explained Ratio 59.04 Component PC284, Cumulative Explained Ratio 59.13 Component PC285, Cumulative Explained Ratio 59.22 Component PC286, Cumulative Explained Ratio 59.32 Component PC287, Cumulative Explained Ratio 59.41 Component PC288, Cumulative Explained Ratio 59.5 Component PC289, Cumulative Explained Ratio 59.59 Component PC290, Cumulative Explained Ratio 59.69 Component PC291, Cumulative Explained Ratio 59.78 Component PC292, Cumulative Explained Ratio 59.87 Component PC293, Cumulative Explained Ratio 59.96 Component PC294, Cumulative Explained Ratio 60.05 Component PC295, Cumulative Explained Ratio 60.15 Component PC296, Cumulative Explained Ratio 60.24 Component PC297, Cumulative Explained Ratio 60.33 Component PC298, Cumulative Explained Ratio 60.42 Component PC299, Cumulative Explained Ratio 60.51 Component PC300, Cumulative Explained Ratio 60.6 Component PC301, Cumulative Explained Ratio 60.69 Component PC302, Cumulative Explained Ratio 60.78 Component PC303, Cumulative Explained Ratio 60.87 Component PC304, Cumulative Explained Ratio 60.96 Component PC305, Cumulative Explained Ratio 61.04 Component PC306, Cumulative Explained Ratio 61.13 Component PC307, Cumulative Explained Ratio 61.22 Component PC308, Cumulative Explained Ratio 61.31 Component PC309, Cumulative Explained Ratio 61.4 Component PC310, Cumulative Explained Ratio 61.48 Component PC311, Cumulative Explained Ratio 61.57 Component PC312, Cumulative Explained Ratio 61.66 Component PC313, Cumulative Explained Ratio 61.74 Component PC314, Cumulative Explained Ratio 61.83 Component PC315, Cumulative Explained Ratio 61.92 Component PC316, Cumulative Explained Ratio 62.0 Component PC317, Cumulative Explained Ratio 62.09 Component PC318, Cumulative Explained Ratio 62.17 Component PC319, Cumulative Explained Ratio 62.26 Component PC320, Cumulative Explained Ratio 62.34 Component PC321, Cumulative Explained Ratio 62.43 Component PC322, Cumulative Explained Ratio 62.51 Component PC323, Cumulative Explained Ratio 62.6 Component PC324, Cumulative Explained Ratio 62.68 Component PC325, Cumulative Explained Ratio 62.77 Component PC326, Cumulative Explained Ratio 62.85 Component PC327, Cumulative Explained Ratio 62.93 Component PC328, Cumulative Explained Ratio 63.02 Component PC329, Cumulative Explained Ratio 63.1 Component PC330, Cumulative Explained Ratio 63.18 Component PC331, Cumulative Explained Ratio 63.27 Component PC332, Cumulative Explained Ratio 63.35 Component PC333, Cumulative Explained Ratio 63.43 Component PC334, Cumulative Explained Ratio 63.51 Component PC335, Cumulative Explained Ratio 63.59 Component PC336, Cumulative Explained Ratio 63.68 Component PC337, Cumulative Explained Ratio 63.76 Component PC338, Cumulative Explained Ratio 63.84 Component PC339, Cumulative Explained Ratio 63.92 Component PC340, Cumulative Explained Ratio 64.0 Component PC341, Cumulative Explained Ratio 64.08 Component PC342, Cumulative Explained Ratio 64.16 Component PC343, Cumulative Explained Ratio 64.24 Component PC344, Cumulative Explained Ratio 64.32 Component PC345, Cumulative Explained Ratio 64.4 Component PC346, Cumulative Explained Ratio 64.48 Component PC347, Cumulative Explained Ratio 64.55 Component PC348, Cumulative Explained Ratio 64.63 Component PC349, Cumulative Explained Ratio 64.71 Component PC350, Cumulative Explained Ratio 64.79 Component PC351, Cumulative Explained Ratio 64.87 Component PC352, Cumulative Explained Ratio 64.94 Component PC353, Cumulative Explained Ratio 65.02 Component PC354, Cumulative Explained Ratio 65.1 Component PC355, Cumulative Explained Ratio 65.17 Component PC356, Cumulative Explained Ratio 65.25 Component PC357, Cumulative Explained Ratio 65.33 Component PC358, Cumulative Explained Ratio 65.4 Component PC359, Cumulative Explained Ratio 65.48 Component PC360, Cumulative Explained Ratio 65.55 Component PC361, Cumulative Explained Ratio 65.63 Component PC362, Cumulative Explained Ratio 65.7 Component PC363, Cumulative Explained Ratio 65.78 Component PC364, Cumulative Explained Ratio 65.85 Component PC365, Cumulative Explained Ratio 65.93 Component PC366, Cumulative Explained Ratio 66.0 Component PC367, Cumulative Explained Ratio 66.08 Component PC368, Cumulative Explained Ratio 66.15 Component PC369, Cumulative Explained Ratio 66.22 Component PC370, Cumulative Explained Ratio 66.3 Component PC371, Cumulative Explained Ratio 66.37 Component PC372, Cumulative Explained Ratio 66.44 Component PC373, Cumulative Explained Ratio 66.52 Component PC374, Cumulative Explained Ratio 66.59 Component PC375, Cumulative Explained Ratio 66.66 Component PC376, Cumulative Explained Ratio 66.73 Component PC377, Cumulative Explained Ratio 66.8 Component PC378, Cumulative Explained Ratio 66.88 Component PC379, Cumulative Explained Ratio 66.95 Component PC380, Cumulative Explained Ratio 67.02 Component PC381, Cumulative Explained Ratio 67.09 Component PC382, Cumulative Explained Ratio 67.16 Component PC383, Cumulative Explained Ratio 67.23 Component PC384, Cumulative Explained Ratio 67.3 Component PC385, Cumulative Explained Ratio 67.37 Component PC386, Cumulative Explained Ratio 67.44 Component PC387, Cumulative Explained Ratio 67.51 Component PC388, Cumulative Explained Ratio 67.58 Component PC389, Cumulative Explained Ratio 67.65 Component PC390, Cumulative Explained Ratio 67.72 Component PC391, Cumulative Explained Ratio 67.79 Component PC392, Cumulative Explained Ratio 67.86 Component PC393, Cumulative Explained Ratio 67.93 Component PC394, Cumulative Explained Ratio 68.0 Component PC395, Cumulative Explained Ratio 68.06 Component PC396, Cumulative Explained Ratio 68.13 Component PC397, Cumulative Explained Ratio 68.2 Component PC398, Cumulative Explained Ratio 68.27 Component PC399, Cumulative Explained Ratio 68.34 Component PC400, Cumulative Explained Ratio 68.4 Component PC401, Cumulative Explained Ratio 68.47 Component PC402, Cumulative Explained Ratio 68.54 Component PC403, Cumulative Explained Ratio 68.6 Component PC404, Cumulative Explained Ratio 68.67 Component PC405, Cumulative Explained Ratio 68.74 Component PC406, Cumulative Explained Ratio 68.8 Component PC407, Cumulative Explained Ratio 68.87 Component PC408, Cumulative Explained Ratio 68.93 Component PC409, Cumulative Explained Ratio 69.0 Component PC410, Cumulative Explained Ratio 69.06 Component PC411, Cumulative Explained Ratio 69.13 Component PC412, Cumulative Explained Ratio 69.2 Component PC413, Cumulative Explained Ratio 69.26 Component PC414, Cumulative Explained Ratio 69.32 Component PC415, Cumulative Explained Ratio 69.39 Component PC416, Cumulative Explained Ratio 69.45 Component PC417, Cumulative Explained Ratio 69.52 Component PC418, Cumulative Explained Ratio 69.58 Component PC419, Cumulative Explained Ratio 69.65 Component PC420, Cumulative Explained Ratio 69.71 Component PC421, Cumulative Explained Ratio 69.77 Component PC422, Cumulative Explained Ratio 69.84 Component PC423, Cumulative Explained Ratio 69.9 Component PC424, Cumulative Explained Ratio 69.96 Component PC425, Cumulative Explained Ratio 70.03 Component PC426, Cumulative Explained Ratio 70.09 Component PC427, Cumulative Explained Ratio 70.15 Component PC428, Cumulative Explained Ratio 70.22 Component PC429, Cumulative Explained Ratio 70.28 Component PC430, Cumulative Explained Ratio 70.34 Component PC431, Cumulative Explained Ratio 70.4 Component PC432, Cumulative Explained Ratio 70.46 Component PC433, Cumulative Explained Ratio 70.53 Component PC434, Cumulative Explained Ratio 70.59 Component PC435, Cumulative Explained Ratio 70.65 Component PC436, Cumulative Explained Ratio 70.71 Component PC437, Cumulative Explained Ratio 70.77 Component PC438, Cumulative Explained Ratio 70.83 Component PC439, Cumulative Explained Ratio 70.89 Component PC440, Cumulative Explained Ratio 70.95 Component PC441, Cumulative Explained Ratio 71.01 Component PC442, Cumulative Explained Ratio 71.07 Component PC443, Cumulative Explained Ratio 71.13 Component PC444, Cumulative Explained Ratio 71.19 Component PC445, Cumulative Explained Ratio 71.25 Component PC446, Cumulative Explained Ratio 71.31 Component PC447, Cumulative Explained Ratio 71.37 Component PC448, Cumulative Explained Ratio 71.43 Component PC449, Cumulative Explained Ratio 71.49 Component PC450, Cumulative Explained Ratio 71.55 Component PC451, Cumulative Explained Ratio 71.61 Component PC452, Cumulative Explained Ratio 71.66 Component PC453, Cumulative Explained Ratio 71.72 Component PC454, Cumulative Explained Ratio 71.78 Component PC455, Cumulative Explained Ratio 71.84 Component PC456, Cumulative Explained Ratio 71.9 Component PC457, Cumulative Explained Ratio 71.95 Component PC458, Cumulative Explained Ratio 72.01 Component PC459, Cumulative Explained Ratio 72.07 Component PC460, Cumulative Explained Ratio 72.12 Component PC461, Cumulative Explained Ratio 72.18 Component PC462, Cumulative Explained Ratio 72.24 Component PC463, Cumulative Explained Ratio 72.3 Component PC464, Cumulative Explained Ratio 72.35 Component PC465, Cumulative Explained Ratio 72.41 Component PC466, Cumulative Explained Ratio 72.47 Component PC467, Cumulative Explained Ratio 72.52 Component PC468, Cumulative Explained Ratio 72.58 Component PC469, Cumulative Explained Ratio 72.63 Component PC470, Cumulative Explained Ratio 72.69 Component PC471, Cumulative Explained Ratio 72.75 Component PC472, Cumulative Explained Ratio 72.8 Component PC473, Cumulative Explained Ratio 72.86 Component PC474, Cumulative Explained Ratio 72.91 Component PC475, Cumulative Explained Ratio 72.97 Component PC476, Cumulative Explained Ratio 73.02 Component PC477, Cumulative Explained Ratio 73.08 Component PC478, Cumulative Explained Ratio 73.14 Component PC479, Cumulative Explained Ratio 73.19 Component PC480, Cumulative Explained Ratio 73.25 Component PC481, Cumulative Explained Ratio 73.3 Component PC482, Cumulative Explained Ratio 73.36 Component PC483, Cumulative Explained Ratio 73.41 Component PC484, Cumulative Explained Ratio 73.47 Component PC485, Cumulative Explained Ratio 73.52 Component PC486, Cumulative Explained Ratio 73.57 Component PC487, Cumulative Explained Ratio 73.63 Component PC488, Cumulative Explained Ratio 73.68 Component PC489, Cumulative Explained Ratio 73.74 Component PC490, Cumulative Explained Ratio 73.79 Component PC491, Cumulative Explained Ratio 73.85 Component PC492, Cumulative Explained Ratio 73.9 Component PC493, Cumulative Explained Ratio 73.95 Component PC494, Cumulative Explained Ratio 74.01 Component PC495, Cumulative Explained Ratio 74.06 Component PC496, Cumulative Explained Ratio 74.11 Component PC497, Cumulative Explained Ratio 74.17 Component PC498, Cumulative Explained Ratio 74.22 Component PC499, Cumulative Explained Ratio 74.27 Component PC500, Cumulative Explained Ratio 74.33 Component PC501, Cumulative Explained Ratio 74.38 Component PC502, Cumulative Explained Ratio 74.43 Component PC503, Cumulative Explained Ratio 74.49 Component PC504, Cumulative Explained Ratio 74.54 Component PC505, Cumulative Explained Ratio 74.59 Component PC506, Cumulative Explained Ratio 74.65 Component PC507, Cumulative Explained Ratio 74.7 Component PC508, Cumulative Explained Ratio 74.75 Component PC509, Cumulative Explained Ratio 74.8 Component PC510, Cumulative Explained Ratio 74.86 Component PC511, Cumulative Explained Ratio 74.91 Component PC512, Cumulative Explained Ratio 74.96 Component PC513, Cumulative Explained Ratio 75.01 Component PC514, Cumulative Explained Ratio 75.07 Component PC515, Cumulative Explained Ratio 75.12 Component PC516, Cumulative Explained Ratio 75.17 Component PC517, Cumulative Explained Ratio 75.22 Component PC518, Cumulative Explained Ratio 75.27 Component PC519, Cumulative Explained Ratio 75.32 Component PC520, Cumulative Explained Ratio 75.38 Component PC521, Cumulative Explained Ratio 75.43 Component PC522, Cumulative Explained Ratio 75.48 Component PC523, Cumulative Explained Ratio 75.53 Component PC524, Cumulative Explained Ratio 75.58 Component PC525, Cumulative Explained Ratio 75.63 Component PC526, Cumulative Explained Ratio 75.68 Component PC527, Cumulative Explained Ratio 75.73 Component PC528, Cumulative Explained Ratio 75.79 Component PC529, Cumulative Explained Ratio 75.84 Component PC530, Cumulative Explained Ratio 75.89 Component PC531, Cumulative Explained Ratio 75.94 Component PC532, Cumulative Explained Ratio 75.99 Component PC533, Cumulative Explained Ratio 76.04 Component PC534, Cumulative Explained Ratio 76.09 Component PC535, Cumulative Explained Ratio 76.14 Component PC536, Cumulative Explained Ratio 76.19 Component PC537, Cumulative Explained Ratio 76.24 Component PC538, Cumulative Explained Ratio 76.29 Component PC539, Cumulative Explained Ratio 76.34 Component PC540, Cumulative Explained Ratio 76.39 Component PC541, Cumulative Explained Ratio 76.44 Component PC542, Cumulative Explained Ratio 76.49 Component PC543, Cumulative Explained Ratio 76.54 Component PC544, Cumulative Explained Ratio 76.59 Component PC545, Cumulative Explained Ratio 76.64 Component PC546, Cumulative Explained Ratio 76.69 Component PC547, Cumulative Explained Ratio 76.74 Component PC548, Cumulative Explained Ratio 76.79 Component PC549, Cumulative Explained Ratio 76.84 Component PC550, Cumulative Explained Ratio 76.89 Component PC551, Cumulative Explained Ratio 76.94 Component PC552, Cumulative Explained Ratio 76.99 Component PC553, Cumulative Explained Ratio 77.04 Component PC554, Cumulative Explained Ratio 77.09 Component PC555, Cumulative Explained Ratio 77.14 Component PC556, Cumulative Explained Ratio 77.18 Component PC557, Cumulative Explained Ratio 77.23 Component PC558, Cumulative Explained Ratio 77.28 Component PC559, Cumulative Explained Ratio 77.33 Component PC560, Cumulative Explained Ratio 77.38 Component PC561, Cumulative Explained Ratio 77.43 Component PC562, Cumulative Explained Ratio 77.48 Component PC563, Cumulative Explained Ratio 77.53 Component PC564, Cumulative Explained Ratio 77.58 Component PC565, Cumulative Explained Ratio 77.63 Component PC566, Cumulative Explained Ratio 77.67 Component PC567, Cumulative Explained Ratio 77.72 Component PC568, Cumulative Explained Ratio 77.77 Component PC569, Cumulative Explained Ratio 77.82 Component PC570, Cumulative Explained Ratio 77.87 Component PC571, Cumulative Explained Ratio 77.92 Component PC572, Cumulative Explained Ratio 77.97 Component PC573, Cumulative Explained Ratio 78.01 Component PC574, Cumulative Explained Ratio 78.06 Component PC575, Cumulative Explained Ratio 78.11 Component PC576, Cumulative Explained Ratio 78.16 Component PC577, Cumulative Explained Ratio 78.21 Component PC578, Cumulative Explained Ratio 78.26 Component PC579, Cumulative Explained Ratio 78.3 Component PC580, Cumulative Explained Ratio 78.35 Component PC581, Cumulative Explained Ratio 78.4 Component PC582, Cumulative Explained Ratio 78.45 Component PC583, Cumulative Explained Ratio 78.5 Component PC584, Cumulative Explained Ratio 78.55 Component PC585, Cumulative Explained Ratio 78.59 Component PC586, Cumulative Explained Ratio 78.64 Component PC587, Cumulative Explained Ratio 78.69 Component PC588, Cumulative Explained Ratio 78.74 Component PC589, Cumulative Explained Ratio 78.79 Component PC590, Cumulative Explained Ratio 78.84 Component PC591, Cumulative Explained Ratio 78.88 Component PC592, Cumulative Explained Ratio 78.93 Component PC593, Cumulative Explained Ratio 78.98 Component PC594, Cumulative Explained Ratio 79.03 Component PC595, Cumulative Explained Ratio 79.08 Component PC596, Cumulative Explained Ratio 79.12 Component PC597, Cumulative Explained Ratio 79.17 Component PC598, Cumulative Explained Ratio 79.22 Component PC599, Cumulative Explained Ratio 79.27 Component PC600, Cumulative Explained Ratio 79.32 Component PC601, Cumulative Explained Ratio 79.36 Component PC602, Cumulative Explained Ratio 79.41 Component PC603, Cumulative Explained Ratio 79.46 Component PC604, Cumulative Explained Ratio 79.51 Component PC605, Cumulative Explained Ratio 79.55 Component PC606, Cumulative Explained Ratio 79.6 Component PC607, Cumulative Explained Ratio 79.65 Component PC608, Cumulative Explained Ratio 79.7 Component PC609, Cumulative Explained Ratio 79.75 Component PC610, Cumulative Explained Ratio 79.79 Component PC611, Cumulative Explained Ratio 79.84 Component PC612, Cumulative Explained Ratio 79.89 Component PC613, Cumulative Explained Ratio 79.94 Component PC614, Cumulative Explained Ratio 79.98 Component PC615, Cumulative Explained Ratio 80.03 Component PC616, Cumulative Explained Ratio 80.08 Component PC617, Cumulative Explained Ratio 80.13 Component PC618, Cumulative Explained Ratio 80.17 Component PC619, Cumulative Explained Ratio 80.22 Component PC620, Cumulative Explained Ratio 80.27 Component PC621, Cumulative Explained Ratio 80.32 Component PC622, Cumulative Explained Ratio 80.36 Component PC623, Cumulative Explained Ratio 80.41 Component PC624, Cumulative Explained Ratio 80.46 Component PC625, Cumulative Explained Ratio 80.5 Component PC626, Cumulative Explained Ratio 80.55 Component PC627, Cumulative Explained Ratio 80.6 Component PC628, Cumulative Explained Ratio 80.64 Component PC629, Cumulative Explained Ratio 80.69 Component PC630, Cumulative Explained Ratio 80.74 Component PC631, Cumulative Explained Ratio 80.79 Component PC632, Cumulative Explained Ratio 80.83 Component PC633, Cumulative Explained Ratio 80.88 Component PC634, Cumulative Explained Ratio 80.93 Component PC635, Cumulative Explained Ratio 80.97 Component PC636, Cumulative Explained Ratio 81.02 Component PC637, Cumulative Explained Ratio 81.07 Component PC638, Cumulative Explained Ratio 81.11 Component PC639, Cumulative Explained Ratio 81.16 Component PC640, Cumulative Explained Ratio 81.2 Component PC641, Cumulative Explained Ratio 81.25 Component PC642, Cumulative Explained Ratio 81.3 Component PC643, Cumulative Explained Ratio 81.34 Component PC644, Cumulative Explained Ratio 81.39 Component PC645, Cumulative Explained Ratio 81.44 Component PC646, Cumulative Explained Ratio 81.48 Component PC647, Cumulative Explained Ratio 81.53 Component PC648, Cumulative Explained Ratio 81.57 Component PC649, Cumulative Explained Ratio 81.62 Component PC650, Cumulative Explained Ratio 81.67 Component PC651, Cumulative Explained Ratio 81.71 Component PC652, Cumulative Explained Ratio 81.76 Component PC653, Cumulative Explained Ratio 81.8 Component PC654, Cumulative Explained Ratio 81.85 Component PC655, Cumulative Explained Ratio 81.89 Component PC656, Cumulative Explained Ratio 81.94 Component PC657, Cumulative Explained Ratio 81.98 Component PC658, Cumulative Explained Ratio 82.03 Component PC659, Cumulative Explained Ratio 82.07 Component PC660, Cumulative Explained Ratio 82.12 Component PC661, Cumulative Explained Ratio 82.16 Component PC662, Cumulative Explained Ratio 82.21 Component PC663, Cumulative Explained Ratio 82.25 Component PC664, Cumulative Explained Ratio 82.3 Component PC665, Cumulative Explained Ratio 82.34 Component PC666, Cumulative Explained Ratio 82.39 Component PC667, Cumulative Explained Ratio 82.43 Component PC668, Cumulative Explained Ratio 82.48 Component PC669, Cumulative Explained Ratio 82.52 Component PC670, Cumulative Explained Ratio 82.57 Component PC671, Cumulative Explained Ratio 82.61 Component PC672, Cumulative Explained Ratio 82.66 Component PC673, Cumulative Explained Ratio 82.7 Component PC674, Cumulative Explained Ratio 82.74 Component PC675, Cumulative Explained Ratio 82.79 Component PC676, Cumulative Explained Ratio 82.83 Component PC677, Cumulative Explained Ratio 82.88 Component PC678, Cumulative Explained Ratio 82.92 Component PC679, Cumulative Explained Ratio 82.96 Component PC680, Cumulative Explained Ratio 83.01 Component PC681, Cumulative Explained Ratio 83.05 Component PC682, Cumulative Explained Ratio 83.09 Component PC683, Cumulative Explained Ratio 83.14 Component PC684, Cumulative Explained Ratio 83.18 Component PC685, Cumulative Explained Ratio 83.23 Component PC686, Cumulative Explained Ratio 83.27 Component PC687, Cumulative Explained Ratio 83.31 Component PC688, Cumulative Explained Ratio 83.36 Component PC689, Cumulative Explained Ratio 83.4 Component PC690, Cumulative Explained Ratio 83.44 Component PC691, Cumulative Explained Ratio 83.48 Component PC692, Cumulative Explained Ratio 83.53 Component PC693, Cumulative Explained Ratio 83.57 Component PC694, Cumulative Explained Ratio 83.61 Component PC695, Cumulative Explained Ratio 83.66 Component PC696, Cumulative Explained Ratio 83.7 Component PC697, Cumulative Explained Ratio 83.74 Component PC698, Cumulative Explained Ratio 83.78 Component PC699, Cumulative Explained Ratio 83.83 Component PC700, Cumulative Explained Ratio 83.87 Component PC701, Cumulative Explained Ratio 83.91 Component PC702, Cumulative Explained Ratio 83.95 Component PC703, Cumulative Explained Ratio 84.0 Component PC704, Cumulative Explained Ratio 84.04 Component PC705, Cumulative Explained Ratio 84.08 Component PC706, Cumulative Explained Ratio 84.12 Component PC707, Cumulative Explained Ratio 84.16 Component PC708, Cumulative Explained Ratio 84.21 Component PC709, Cumulative Explained Ratio 84.25 Component PC710, Cumulative Explained Ratio 84.29 Component PC711, Cumulative Explained Ratio 84.33 Component PC712, Cumulative Explained Ratio 84.37 Component PC713, Cumulative Explained Ratio 84.41 Component PC714, Cumulative Explained Ratio 84.45 Component PC715, Cumulative Explained Ratio 84.5 Component PC716, Cumulative Explained Ratio 84.54 Component PC717, Cumulative Explained Ratio 84.58 Component PC718, Cumulative Explained Ratio 84.62 Component PC719, Cumulative Explained Ratio 84.66 Component PC720, Cumulative Explained Ratio 84.7 Component PC721, Cumulative Explained Ratio 84.74 Component PC722, Cumulative Explained Ratio 84.78 Component PC723, Cumulative Explained Ratio 84.82 Component PC724, Cumulative Explained Ratio 84.87 Component PC725, Cumulative Explained Ratio 84.91 Component PC726, Cumulative Explained Ratio 84.95 Component PC727, Cumulative Explained Ratio 84.99 Component PC728, Cumulative Explained Ratio 85.03 Component PC729, Cumulative Explained Ratio 85.07 Component PC730, Cumulative Explained Ratio 85.11 Component PC731, Cumulative Explained Ratio 85.15 Component PC732, Cumulative Explained Ratio 85.19 Component PC733, Cumulative Explained Ratio 85.23 Component PC734, Cumulative Explained Ratio 85.27 Component PC735, Cumulative Explained Ratio 85.31 Component PC736, Cumulative Explained Ratio 85.35 Component PC737, Cumulative Explained Ratio 85.39 Component PC738, Cumulative Explained Ratio 85.43 Component PC739, Cumulative Explained Ratio 85.47 Component PC740, Cumulative Explained Ratio 85.51 Component PC741, Cumulative Explained Ratio 85.55 Component PC742, Cumulative Explained Ratio 85.59 Component PC743, Cumulative Explained Ratio 85.63 Component PC744, Cumulative Explained Ratio 85.67 Component PC745, Cumulative Explained Ratio 85.7 Component PC746, Cumulative Explained Ratio 85.74 Component PC747, Cumulative Explained Ratio 85.78 Component PC748, Cumulative Explained Ratio 85.82 Component PC749, Cumulative Explained Ratio 85.86 Component PC750, Cumulative Explained Ratio 85.9 Component PC751, Cumulative Explained Ratio 85.94 Component PC752, Cumulative Explained Ratio 85.98 Component PC753, Cumulative Explained Ratio 86.01 Component PC754, Cumulative Explained Ratio 86.05 Component PC755, Cumulative Explained Ratio 86.09 Component PC756, Cumulative Explained Ratio 86.13 Component PC757, Cumulative Explained Ratio 86.17 Component PC758, Cumulative Explained Ratio 86.21 Component PC759, Cumulative Explained Ratio 86.24 Component PC760, Cumulative Explained Ratio 86.28 Component PC761, Cumulative Explained Ratio 86.32 Component PC762, Cumulative Explained Ratio 86.36 Component PC763, Cumulative Explained Ratio 86.4 Component PC764, Cumulative Explained Ratio 86.43 Component PC765, Cumulative Explained Ratio 86.47 Component PC766, Cumulative Explained Ratio 86.51 Component PC767, Cumulative Explained Ratio 86.55 Component PC768, Cumulative Explained Ratio 86.58 Component PC769, Cumulative Explained Ratio 86.62 Component PC770, Cumulative Explained Ratio 86.66 Component PC771, Cumulative Explained Ratio 86.7 Component PC772, Cumulative Explained Ratio 86.73 Component PC773, Cumulative Explained Ratio 86.77 Component PC774, Cumulative Explained Ratio 86.81 Component PC775, Cumulative Explained Ratio 86.84 Component PC776, Cumulative Explained Ratio 86.88 Component PC777, Cumulative Explained Ratio 86.92 Component PC778, Cumulative Explained Ratio 86.95 Component PC779, Cumulative Explained Ratio 86.99 Component PC780, Cumulative Explained Ratio 87.03 Component PC781, Cumulative Explained Ratio 87.06 Component PC782, Cumulative Explained Ratio 87.1 Component PC783, Cumulative Explained Ratio 87.14 Component PC784, Cumulative Explained Ratio 87.17 Component PC785, Cumulative Explained Ratio 87.21 Component PC786, Cumulative Explained Ratio 87.25 Component PC787, Cumulative Explained Ratio 87.28 Component PC788, Cumulative Explained Ratio 87.32 Component PC789, Cumulative Explained Ratio 87.35 Component PC790, Cumulative Explained Ratio 87.39 Component PC791, Cumulative Explained Ratio 87.43 Component PC792, Cumulative Explained Ratio 87.46 Component PC793, Cumulative Explained Ratio 87.5 Component PC794, Cumulative Explained Ratio 87.53 Component PC795, Cumulative Explained Ratio 87.57 Component PC796, Cumulative Explained Ratio 87.6 Component PC797, Cumulative Explained Ratio 87.64 Component PC798, Cumulative Explained Ratio 87.67 Component PC799, Cumulative Explained Ratio 87.71 Component PC800, Cumulative Explained Ratio 87.74 Component PC801, Cumulative Explained Ratio 87.78 Component PC802, Cumulative Explained Ratio 87.81 Component PC803, Cumulative Explained Ratio 87.85 Component PC804, Cumulative Explained Ratio 87.88 Component PC805, Cumulative Explained Ratio 87.92 Component PC806, Cumulative Explained Ratio 87.95 Component PC807, Cumulative Explained Ratio 87.99 Component PC808, Cumulative Explained Ratio 88.02 Component PC809, Cumulative Explained Ratio 88.06 Component PC810, Cumulative Explained Ratio 88.09 Component PC811, Cumulative Explained Ratio 88.13 Component PC812, Cumulative Explained Ratio 88.16 Component PC813, Cumulative Explained Ratio 88.19 Component PC814, Cumulative Explained Ratio 88.23 Component PC815, Cumulative Explained Ratio 88.26 Component PC816, Cumulative Explained Ratio 88.3 Component PC817, Cumulative Explained Ratio 88.33 Component PC818, Cumulative Explained Ratio 88.37 Component PC819, Cumulative Explained Ratio 88.4 Component PC820, Cumulative Explained Ratio 88.43 Component PC821, Cumulative Explained Ratio 88.47 Component PC822, Cumulative Explained Ratio 88.5 Component PC823, Cumulative Explained Ratio 88.53 Component PC824, Cumulative Explained Ratio 88.57 Component PC825, Cumulative Explained Ratio 88.6 Component PC826, Cumulative Explained Ratio 88.64 Component PC827, Cumulative Explained Ratio 88.67 Component PC828, Cumulative Explained Ratio 88.7 Component PC829, Cumulative Explained Ratio 88.74 Component PC830, Cumulative Explained Ratio 88.77 Component PC831, Cumulative Explained Ratio 88.8 Component PC832, Cumulative Explained Ratio 88.83 Component PC833, Cumulative Explained Ratio 88.87 Component PC834, Cumulative Explained Ratio 88.9 Component PC835, Cumulative Explained Ratio 88.93 Component PC836, Cumulative Explained Ratio 88.97 Component PC837, Cumulative Explained Ratio 89.0 Component PC838, Cumulative Explained Ratio 89.03 Component PC839, Cumulative Explained Ratio 89.06 Component PC840, Cumulative Explained Ratio 89.1 Component PC841, Cumulative Explained Ratio 89.13 Component PC842, Cumulative Explained Ratio 89.16 Component PC843, Cumulative Explained Ratio 89.19 Component PC844, Cumulative Explained Ratio 89.23 Component PC845, Cumulative Explained Ratio 89.26 Component PC846, Cumulative Explained Ratio 89.29 Component PC847, Cumulative Explained Ratio 89.32 Component PC848, Cumulative Explained Ratio 89.36 Component PC849, Cumulative Explained Ratio 89.39 Component PC850, Cumulative Explained Ratio 89.42 Component PC851, Cumulative Explained Ratio 89.45 Component PC852, Cumulative Explained Ratio 89.48 Component PC853, Cumulative Explained Ratio 89.51 Component PC854, Cumulative Explained Ratio 89.55 Component PC855, Cumulative Explained Ratio 89.58 Component PC856, Cumulative Explained Ratio 89.61 Component PC857, Cumulative Explained Ratio 89.64 Component PC858, Cumulative Explained Ratio 89.67 Component PC859, Cumulative Explained Ratio 89.7 Component PC860, Cumulative Explained Ratio 89.73 Component PC861, Cumulative Explained Ratio 89.76 Component PC862, Cumulative Explained Ratio 89.8 Component PC863, Cumulative Explained Ratio 89.83 Component PC864, Cumulative Explained Ratio 89.86 Component PC865, Cumulative Explained Ratio 89.89 Component PC866, Cumulative Explained Ratio 89.92 Component PC867, Cumulative Explained Ratio 89.95 Component PC868, Cumulative Explained Ratio 89.98 Component PC869, Cumulative Explained Ratio 90.01 Component PC870, Cumulative Explained Ratio 90.04 Component PC871, Cumulative Explained Ratio 90.07 Component PC872, Cumulative Explained Ratio 90.1 Component PC873, Cumulative Explained Ratio 90.13 Component PC874, Cumulative Explained Ratio 90.16 Component PC875, Cumulative Explained Ratio 90.19 Component PC876, Cumulative Explained Ratio 90.22 Component PC877, Cumulative Explained Ratio 90.26 Component PC878, Cumulative Explained Ratio 90.29 Component PC879, Cumulative Explained Ratio 90.32 Component PC880, Cumulative Explained Ratio 90.35 Component PC881, Cumulative Explained Ratio 90.38 Component PC882, Cumulative Explained Ratio 90.41 Component PC883, Cumulative Explained Ratio 90.43 Component PC884, Cumulative Explained Ratio 90.46 Component PC885, Cumulative Explained Ratio 90.49 Component PC886, Cumulative Explained Ratio 90.52 Component PC887, Cumulative Explained Ratio 90.55 Component PC888, Cumulative Explained Ratio 90.58 Component PC889, Cumulative Explained Ratio 90.61 Component PC890, Cumulative Explained Ratio 90.64 Component PC891, Cumulative Explained Ratio 90.67 Component PC892, Cumulative Explained Ratio 90.7 Component PC893, Cumulative Explained Ratio 90.73 Component PC894, Cumulative Explained Ratio 90.76 Component PC895, Cumulative Explained Ratio 90.79 Component PC896, Cumulative Explained Ratio 90.82 Component PC897, Cumulative Explained Ratio 90.85 Component PC898, Cumulative Explained Ratio 90.87 Component PC899, Cumulative Explained Ratio 90.9 Component PC900, Cumulative Explained Ratio 90.93 Component PC901, Cumulative Explained Ratio 90.96 Component PC902, Cumulative Explained Ratio 90.99 Component PC903, Cumulative Explained Ratio 91.02 Component PC904, Cumulative Explained Ratio 91.05 Component PC905, Cumulative Explained Ratio 91.08 Component PC906, Cumulative Explained Ratio 91.1 Component PC907, Cumulative Explained Ratio 91.13 Component PC908, Cumulative Explained Ratio 91.16 Component PC909, Cumulative Explained Ratio 91.19 Component PC910, Cumulative Explained Ratio 91.22 Component PC911, Cumulative Explained Ratio 91.25 Component PC912, Cumulative Explained Ratio 91.27 Component PC913, Cumulative Explained Ratio 91.3 Component PC914, Cumulative Explained Ratio 91.33 Component PC915, Cumulative Explained Ratio 91.36 Component PC916, Cumulative Explained Ratio 91.38 Component PC917, Cumulative Explained Ratio 91.41 Component PC918, Cumulative Explained Ratio 91.44 Component PC919, Cumulative Explained Ratio 91.47 Component PC920, Cumulative Explained Ratio 91.5 Component PC921, Cumulative Explained Ratio 91.52 Component PC922, Cumulative Explained Ratio 91.55 Component PC923, Cumulative Explained Ratio 91.58 Component PC924, Cumulative Explained Ratio 91.6 Component PC925, Cumulative Explained Ratio 91.63 Component PC926, Cumulative Explained Ratio 91.66 Component PC927, Cumulative Explained Ratio 91.69 Component PC928, Cumulative Explained Ratio 91.71 Component PC929, Cumulative Explained Ratio 91.74 Component PC930, Cumulative Explained Ratio 91.77 Component PC931, Cumulative Explained Ratio 91.79 Component PC932, Cumulative Explained Ratio 91.82 Component PC933, Cumulative Explained Ratio 91.85 Component PC934, Cumulative Explained Ratio 91.87 Component PC935, Cumulative Explained Ratio 91.9 Component PC936, Cumulative Explained Ratio 91.93 Component PC937, Cumulative Explained Ratio 91.95 Component PC938, Cumulative Explained Ratio 91.98 Component PC939, Cumulative Explained Ratio 92.01 Component PC940, Cumulative Explained Ratio 92.03 Component PC941, Cumulative Explained Ratio 92.06 Component PC942, Cumulative Explained Ratio 92.09 Component PC943, Cumulative Explained Ratio 92.11 Component PC944, Cumulative Explained Ratio 92.14 Component PC945, Cumulative Explained Ratio 92.16 Component PC946, Cumulative Explained Ratio 92.19 Component PC947, Cumulative Explained Ratio 92.22 Component PC948, Cumulative Explained Ratio 92.24 Component PC949, Cumulative Explained Ratio 92.27 Component PC950, Cumulative Explained Ratio 92.29 Component PC951, Cumulative Explained Ratio 92.32 Component PC952, Cumulative Explained Ratio 92.34 Component PC953, Cumulative Explained Ratio 92.37 Component PC954, Cumulative Explained Ratio 92.4 Component PC955, Cumulative Explained Ratio 92.42 Component PC956, Cumulative Explained Ratio 92.45 Component PC957, Cumulative Explained Ratio 92.47 Component PC958, Cumulative Explained Ratio 92.5 Component PC959, Cumulative Explained Ratio 92.52 Component PC960, Cumulative Explained Ratio 92.55 Component PC961, Cumulative Explained Ratio 92.57 Component PC962, Cumulative Explained Ratio 92.6 Component PC963, Cumulative Explained Ratio 92.62 Component PC964, Cumulative Explained Ratio 92.65 Component PC965, Cumulative Explained Ratio 92.67 Component PC966, Cumulative Explained Ratio 92.7 Component PC967, Cumulative Explained Ratio 92.72 Component PC968, Cumulative Explained Ratio 92.74 Component PC969, Cumulative Explained Ratio 92.77 Component PC970, Cumulative Explained Ratio 92.79 Component PC971, Cumulative Explained Ratio 92.82 Component PC972, Cumulative Explained Ratio 92.84 Component PC973, Cumulative Explained Ratio 92.87 Component PC974, Cumulative Explained Ratio 92.89 Component PC975, Cumulative Explained Ratio 92.91 Component PC976, Cumulative Explained Ratio 92.94 Component PC977, Cumulative Explained Ratio 92.96 Component PC978, Cumulative Explained Ratio 92.99 Component PC979, Cumulative Explained Ratio 93.01 Component PC980, Cumulative Explained Ratio 93.03 Component PC981, Cumulative Explained Ratio 93.06 Component PC982, Cumulative Explained Ratio 93.08 Component PC983, Cumulative Explained Ratio 93.1 Component PC984, Cumulative Explained Ratio 93.13 Component PC985, Cumulative Explained Ratio 93.15 Component PC986, Cumulative Explained Ratio 93.17 Component PC987, Cumulative Explained Ratio 93.2 Component PC988, Cumulative Explained Ratio 93.22 Component PC989, Cumulative Explained Ratio 93.24 Component PC990, Cumulative Explained Ratio 93.27 Component PC991, Cumulative Explained Ratio 93.29 Component PC992, Cumulative Explained Ratio 93.31 Component PC993, Cumulative Explained Ratio 93.34 Component PC994, Cumulative Explained Ratio 93.36 Component PC995, Cumulative Explained Ratio 93.38 Component PC996, Cumulative Explained Ratio 93.4 Component PC997, Cumulative Explained Ratio 93.43 Component PC998, Cumulative Explained Ratio 93.45 Component PC999, Cumulative Explained Ratio 93.47 Component PC1000, Cumulative Explained Ratio 93.49 Component PC1001, Cumulative Explained Ratio 93.52 Component PC1002, Cumulative Explained Ratio 93.54 Component PC1003, Cumulative Explained Ratio 93.56 Component PC1004, Cumulative Explained Ratio 93.58 Component PC1005, Cumulative Explained Ratio 93.61 Component PC1006, Cumulative Explained Ratio 93.63 Component PC1007, Cumulative Explained Ratio 93.65 Component PC1008, Cumulative Explained Ratio 93.67 Component PC1009, Cumulative Explained Ratio 93.69 Component PC1010, Cumulative Explained Ratio 93.71 Component PC1011, Cumulative Explained Ratio 93.74 Component PC1012, Cumulative Explained Ratio 93.76 Component PC1013, Cumulative Explained Ratio 93.78 Component PC1014, Cumulative Explained Ratio 93.8 Component PC1015, Cumulative Explained Ratio 93.82 Component PC1016, Cumulative Explained Ratio 93.84 Component PC1017, Cumulative Explained Ratio 93.87 Component PC1018, Cumulative Explained Ratio 93.89 Component PC1019, Cumulative Explained Ratio 93.91 Component PC1020, Cumulative Explained Ratio 93.93 Component PC1021, Cumulative Explained Ratio 93.95 Component PC1022, Cumulative Explained Ratio 93.97 Component PC1023, Cumulative Explained Ratio 93.99 Component PC1024, Cumulative Explained Ratio 94.02 Component PC1025, Cumulative Explained Ratio 94.04 Component PC1026, Cumulative Explained Ratio 94.06 Component PC1027, Cumulative Explained Ratio 94.08 Component PC1028, Cumulative Explained Ratio 94.1 Component PC1029, Cumulative Explained Ratio 94.12 Component PC1030, Cumulative Explained Ratio 94.14 Component PC1031, Cumulative Explained Ratio 94.16 Component PC1032, Cumulative Explained Ratio 94.18 Component PC1033, Cumulative Explained Ratio 94.2 Component PC1034, Cumulative Explained Ratio 94.22 Component PC1035, Cumulative Explained Ratio 94.24 Component PC1036, Cumulative Explained Ratio 94.26 Component PC1037, Cumulative Explained Ratio 94.28 Component PC1038, Cumulative Explained Ratio 94.3 Component PC1039, Cumulative Explained Ratio 94.32 Component PC1040, Cumulative Explained Ratio 94.34 Component PC1041, Cumulative Explained Ratio 94.36 Component PC1042, Cumulative Explained Ratio 94.38 Component PC1043, Cumulative Explained Ratio 94.4 Component PC1044, Cumulative Explained Ratio 94.42 Component PC1045, Cumulative Explained Ratio 94.44 Component PC1046, Cumulative Explained Ratio 94.46 Component PC1047, Cumulative Explained Ratio 94.48 Component PC1048, Cumulative Explained Ratio 94.5 Component PC1049, Cumulative Explained Ratio 94.52 Component PC1050, Cumulative Explained Ratio 94.54 Component PC1051, Cumulative Explained Ratio 94.56 Component PC1052, Cumulative Explained Ratio 94.58 Component PC1053, Cumulative Explained Ratio 94.6 Component PC1054, Cumulative Explained Ratio 94.62 Component PC1055, Cumulative Explained Ratio 94.64 Component PC1056, Cumulative Explained Ratio 94.66 Component PC1057, Cumulative Explained Ratio 94.68 Component PC1058, Cumulative Explained Ratio 94.7 Component PC1059, Cumulative Explained Ratio 94.72 Component PC1060, Cumulative Explained Ratio 94.74 Component PC1061, Cumulative Explained Ratio 94.75 Component PC1062, Cumulative Explained Ratio 94.77 Component PC1063, Cumulative Explained Ratio 94.79 Component PC1064, Cumulative Explained Ratio 94.81 Component PC1065, Cumulative Explained Ratio 94.83 Component PC1066, Cumulative Explained Ratio 94.85 Component PC1067, Cumulative Explained Ratio 94.87 Component PC1068, Cumulative Explained Ratio 94.89 Component PC1069, Cumulative Explained Ratio 94.9 Component PC1070, Cumulative Explained Ratio 94.92 Component PC1071, Cumulative Explained Ratio 94.94 Component PC1072, Cumulative Explained Ratio 94.96 Component PC1073, Cumulative Explained Ratio 94.98 Component PC1074, Cumulative Explained Ratio 95.0 Component PC1075, Cumulative Explained Ratio 95.02 Component PC1076, Cumulative Explained Ratio 95.03 Component PC1077, Cumulative Explained Ratio 95.05 Component PC1078, Cumulative Explained Ratio 95.07 Component PC1079, Cumulative Explained Ratio 95.09 Component PC1080, Cumulative Explained Ratio 95.11 Component PC1081, Cumulative Explained Ratio 95.12 Component PC1082, Cumulative Explained Ratio 95.14 Component PC1083, Cumulative Explained Ratio 95.16 Component PC1084, Cumulative Explained Ratio 95.18 Component PC1085, Cumulative Explained Ratio 95.19 Component PC1086, Cumulative Explained Ratio 95.21 Component PC1087, Cumulative Explained Ratio 95.23 Component PC1088, Cumulative Explained Ratio 95.25 Component PC1089, Cumulative Explained Ratio 95.26 Component PC1090, Cumulative Explained Ratio 95.28 Component PC1091, Cumulative Explained Ratio 95.3 Component PC1092, Cumulative Explained Ratio 95.32 Component PC1093, Cumulative Explained Ratio 95.33 Component PC1094, Cumulative Explained Ratio 95.35 Component PC1095, Cumulative Explained Ratio 95.37 Component PC1096, Cumulative Explained Ratio 95.38 Component PC1097, Cumulative Explained Ratio 95.4 Component PC1098, Cumulative Explained Ratio 95.42 Component PC1099, Cumulative Explained Ratio 95.43 Component PC1100, Cumulative Explained Ratio 95.45 Component PC1101, Cumulative Explained Ratio 95.47 Component PC1102, Cumulative Explained Ratio 95.49 Component PC1103, Cumulative Explained Ratio 95.5 Component PC1104, Cumulative Explained Ratio 95.52 Component PC1105, Cumulative Explained Ratio 95.54 Component PC1106, Cumulative Explained Ratio 95.55 Component PC1107, Cumulative Explained Ratio 95.57 Component PC1108, Cumulative Explained Ratio 95.59 Component PC1109, Cumulative Explained Ratio 95.6 Component PC1110, Cumulative Explained Ratio 95.62 Component PC1111, Cumulative Explained Ratio 95.63 Component PC1112, Cumulative Explained Ratio 95.65 Component PC1113, Cumulative Explained Ratio 95.67 Component PC1114, Cumulative Explained Ratio 95.68 Component PC1115, Cumulative Explained Ratio 95.7 Component PC1116, Cumulative Explained Ratio 95.72 Component PC1117, Cumulative Explained Ratio 95.73 Component PC1118, Cumulative Explained Ratio 95.75 Component PC1119, Cumulative Explained Ratio 95.76 Component PC1120, Cumulative Explained Ratio 95.78 Component PC1121, Cumulative Explained Ratio 95.8 Component PC1122, Cumulative Explained Ratio 95.81 Component PC1123, Cumulative Explained Ratio 95.83 Component PC1124, Cumulative Explained Ratio 95.84 Component PC1125, Cumulative Explained Ratio 95.86 Component PC1126, Cumulative Explained Ratio 95.88 Component PC1127, Cumulative Explained Ratio 95.89 Component PC1128, Cumulative Explained Ratio 95.91 Component PC1129, Cumulative Explained Ratio 95.92 Component PC1130, Cumulative Explained Ratio 95.94 Component PC1131, Cumulative Explained Ratio 95.95 Component PC1132, Cumulative Explained Ratio 95.97 Component PC1133, Cumulative Explained Ratio 95.98 Component PC1134, Cumulative Explained Ratio 96.0 Component PC1135, Cumulative Explained Ratio 96.01 Component PC1136, Cumulative Explained Ratio 96.03 Component PC1137, Cumulative Explained Ratio 96.05 Component PC1138, Cumulative Explained Ratio 96.06 Component PC1139, Cumulative Explained Ratio 96.08 Component PC1140, Cumulative Explained Ratio 96.09 Component PC1141, Cumulative Explained Ratio 96.11 Component PC1142, Cumulative Explained Ratio 96.12 Component PC1143, Cumulative Explained Ratio 96.14 Component PC1144, Cumulative Explained Ratio 96.15 Component PC1145, Cumulative Explained Ratio 96.16 Component PC1146, Cumulative Explained Ratio 96.18 Component PC1147, Cumulative Explained Ratio 96.19 Component PC1148, Cumulative Explained Ratio 96.21 Component PC1149, Cumulative Explained Ratio 96.22 Component PC1150, Cumulative Explained Ratio 96.24 Component PC1151, Cumulative Explained Ratio 96.25 Component PC1152, Cumulative Explained Ratio 96.27 Component PC1153, Cumulative Explained Ratio 96.28 Component PC1154, Cumulative Explained Ratio 96.3 Component PC1155, Cumulative Explained Ratio 96.31 Component PC1156, Cumulative Explained Ratio 96.32 Component PC1157, Cumulative Explained Ratio 96.34 Component PC1158, Cumulative Explained Ratio 96.35 Component PC1159, Cumulative Explained Ratio 96.37 Component PC1160, Cumulative Explained Ratio 96.38 Component PC1161, Cumulative Explained Ratio 96.39 Component PC1162, Cumulative Explained Ratio 96.41 Component PC1163, Cumulative Explained Ratio 96.42 Component PC1164, Cumulative Explained Ratio 96.44 Component PC1165, Cumulative Explained Ratio 96.45 Component PC1166, Cumulative Explained Ratio 96.46 Component PC1167, Cumulative Explained Ratio 96.48 Component PC1168, Cumulative Explained Ratio 96.49 Component PC1169, Cumulative Explained Ratio 96.51 Component PC1170, Cumulative Explained Ratio 96.52 Component PC1171, Cumulative Explained Ratio 96.53 Component PC1172, Cumulative Explained Ratio 96.55 Component PC1173, Cumulative Explained Ratio 96.56 Component PC1174, Cumulative Explained Ratio 96.57 Component PC1175, Cumulative Explained Ratio 96.59 Component PC1176, Cumulative Explained Ratio 96.6 Component PC1177, Cumulative Explained Ratio 96.61 Component PC1178, Cumulative Explained Ratio 96.63 Component PC1179, Cumulative Explained Ratio 96.64 Component PC1180, Cumulative Explained Ratio 96.65 Component PC1181, Cumulative Explained Ratio 96.67 Component PC1182, Cumulative Explained Ratio 96.68 Component PC1183, Cumulative Explained Ratio 96.69 Component PC1184, Cumulative Explained Ratio 96.71 Component PC1185, Cumulative Explained Ratio 96.72 Component PC1186, Cumulative Explained Ratio 96.73 Component PC1187, Cumulative Explained Ratio 96.74 Component PC1188, Cumulative Explained Ratio 96.76 Component PC1189, Cumulative Explained Ratio 96.77 Component PC1190, Cumulative Explained Ratio 96.78 Component PC1191, Cumulative Explained Ratio 96.8 Component PC1192, Cumulative Explained Ratio 96.81 Component PC1193, Cumulative Explained Ratio 96.82 Component PC1194, Cumulative Explained Ratio 96.83 Component PC1195, Cumulative Explained Ratio 96.85 Component PC1196, Cumulative Explained Ratio 96.86 Component PC1197, Cumulative Explained Ratio 96.87 Component PC1198, Cumulative Explained Ratio 96.88 Component PC1199, Cumulative Explained Ratio 96.9 Component PC1200, Cumulative Explained Ratio 96.91 Component PC1201, Cumulative Explained Ratio 96.92 Component PC1202, Cumulative Explained Ratio 96.93 Component PC1203, Cumulative Explained Ratio 96.95 Component PC1204, Cumulative Explained Ratio 96.96 Component PC1205, Cumulative Explained Ratio 96.97 Component PC1206, Cumulative Explained Ratio 96.98 Component PC1207, Cumulative Explained Ratio 97.0 Component PC1208, Cumulative Explained Ratio 97.01 Component PC1209, Cumulative Explained Ratio 97.02 Component PC1210, Cumulative Explained Ratio 97.03 Component PC1211, Cumulative Explained Ratio 97.04 Component PC1212, Cumulative Explained Ratio 97.06 Component PC1213, Cumulative Explained Ratio 97.07 Component PC1214, Cumulative Explained Ratio 97.08 Component PC1215, Cumulative Explained Ratio 97.09 Component PC1216, Cumulative Explained Ratio 97.1 Component PC1217, Cumulative Explained Ratio 97.12 Component PC1218, Cumulative Explained Ratio 97.13 Component PC1219, Cumulative Explained Ratio 97.14 Component PC1220, Cumulative Explained Ratio 97.15 Component PC1221, Cumulative Explained Ratio 97.16 Component PC1222, Cumulative Explained Ratio 97.17 Component PC1223, Cumulative Explained Ratio 97.19 Component PC1224, Cumulative Explained Ratio 97.2 Component PC1225, Cumulative Explained Ratio 97.21 Component PC1226, Cumulative Explained Ratio 97.22 Component PC1227, Cumulative Explained Ratio 97.23 Component PC1228, Cumulative Explained Ratio 97.24 Component PC1229, Cumulative Explained Ratio 97.25 Component PC1230, Cumulative Explained Ratio 97.27 Component PC1231, Cumulative Explained Ratio 97.28 Component PC1232, Cumulative Explained Ratio 97.29 Component PC1233, Cumulative Explained Ratio 97.3 Component PC1234, Cumulative Explained Ratio 97.31 Component PC1235, Cumulative Explained Ratio 97.32 Component PC1236, Cumulative Explained Ratio 97.33 Component PC1237, Cumulative Explained Ratio 97.34 Component PC1238, Cumulative Explained Ratio 97.35 Component PC1239, Cumulative Explained Ratio 97.37 Component PC1240, Cumulative Explained Ratio 97.38 Component PC1241, Cumulative Explained Ratio 97.39 Component PC1242, Cumulative Explained Ratio 97.4 Component PC1243, Cumulative Explained Ratio 97.41 Component PC1244, Cumulative Explained Ratio 97.42 Component PC1245, Cumulative Explained Ratio 97.43 Component PC1246, Cumulative Explained Ratio 97.44 Component PC1247, Cumulative Explained Ratio 97.45 Component PC1248, Cumulative Explained Ratio 97.46 Component PC1249, Cumulative Explained Ratio 97.47 Component PC1250, Cumulative Explained Ratio 97.48 Component PC1251, Cumulative Explained Ratio 97.49 Component PC1252, Cumulative Explained Ratio 97.5 Component PC1253, Cumulative Explained Ratio 97.52 Component PC1254, Cumulative Explained Ratio 97.53 Component PC1255, Cumulative Explained Ratio 97.54 Component PC1256, Cumulative Explained Ratio 97.55 Component PC1257, Cumulative Explained Ratio 97.56 Component PC1258, Cumulative Explained Ratio 97.57 Component PC1259, Cumulative Explained Ratio 97.58 Component PC1260, Cumulative Explained Ratio 97.59 Component PC1261, Cumulative Explained Ratio 97.6 Component PC1262, Cumulative Explained Ratio 97.61 Component PC1263, Cumulative Explained Ratio 97.62 Component PC1264, Cumulative Explained Ratio 97.63 Component PC1265, Cumulative Explained Ratio 97.64 Component PC1266, Cumulative Explained Ratio 97.65 Component PC1267, Cumulative Explained Ratio 97.66 Component PC1268, Cumulative Explained Ratio 97.67 Component PC1269, Cumulative Explained Ratio 97.68 Component PC1270, Cumulative Explained Ratio 97.69 Component PC1271, Cumulative Explained Ratio 97.7 Component PC1272, Cumulative Explained Ratio 97.71 Component PC1273, Cumulative Explained Ratio 97.72 Component PC1274, Cumulative Explained Ratio 97.73 Component PC1275, Cumulative Explained Ratio 97.74 Component PC1276, Cumulative Explained Ratio 97.75 Component PC1277, Cumulative Explained Ratio 97.76 Component PC1278, Cumulative Explained Ratio 97.77 Component PC1279, Cumulative Explained Ratio 97.78 Component PC1280, Cumulative Explained Ratio 97.79 Component PC1281, Cumulative Explained Ratio 97.8 Component PC1282, Cumulative Explained Ratio 97.8 Component PC1283, Cumulative Explained Ratio 97.81 Component PC1284, Cumulative Explained Ratio 97.82 Component PC1285, Cumulative Explained Ratio 97.83 Component PC1286, Cumulative Explained Ratio 97.84 Component PC1287, Cumulative Explained Ratio 97.85 Component PC1288, Cumulative Explained Ratio 97.86 Component PC1289, Cumulative Explained Ratio 97.87 Component PC1290, Cumulative Explained Ratio 97.88 Component PC1291, Cumulative Explained Ratio 97.89 Component PC1292, Cumulative Explained Ratio 97.9 Component PC1293, Cumulative Explained Ratio 97.91 Component PC1294, Cumulative Explained Ratio 97.92 Component PC1295, Cumulative Explained Ratio 97.93 Component PC1296, Cumulative Explained Ratio 97.94 Component PC1297, Cumulative Explained Ratio 97.94 Component PC1298, Cumulative Explained Ratio 97.95 Component PC1299, Cumulative Explained Ratio 97.96 Component PC1300, Cumulative Explained Ratio 97.97 Component PC1301, Cumulative Explained Ratio 97.98 Component PC1302, Cumulative Explained Ratio 97.99 Component PC1303, Cumulative Explained Ratio 98.0 Component PC1304, Cumulative Explained Ratio 98.01 Component PC1305, Cumulative Explained Ratio 98.02 Component PC1306, Cumulative Explained Ratio 98.02 Component PC1307, Cumulative Explained Ratio 98.03 Component PC1308, Cumulative Explained Ratio 98.04 Component PC1309, Cumulative Explained Ratio 98.05 Component PC1310, Cumulative Explained Ratio 98.06 Component PC1311, Cumulative Explained Ratio 98.07 Component PC1312, Cumulative Explained Ratio 98.08 Component PC1313, Cumulative Explained Ratio 98.09 Component PC1314, Cumulative Explained Ratio 98.09 Component PC1315, Cumulative Explained Ratio 98.1 Component PC1316, Cumulative Explained Ratio 98.11 Component PC1317, Cumulative Explained Ratio 98.12 Component PC1318, Cumulative Explained Ratio 98.13 Component PC1319, Cumulative Explained Ratio 98.14 Component PC1320, Cumulative Explained Ratio 98.15 Component PC1321, Cumulative Explained Ratio 98.15 Component PC1322, Cumulative Explained Ratio 98.16 Component PC1323, Cumulative Explained Ratio 98.17 Component PC1324, Cumulative Explained Ratio 98.18 Component PC1325, Cumulative Explained Ratio 98.19 Component PC1326, Cumulative Explained Ratio 98.19 Component PC1327, Cumulative Explained Ratio 98.2 Component PC1328, Cumulative Explained Ratio 98.21 Component PC1329, Cumulative Explained Ratio 98.22 Component PC1330, Cumulative Explained Ratio 98.23 Component PC1331, Cumulative Explained Ratio 98.24 Component PC1332, Cumulative Explained Ratio 98.24 Component PC1333, Cumulative Explained Ratio 98.25 Component PC1334, Cumulative Explained Ratio 98.26 Component PC1335, Cumulative Explained Ratio 98.27 Component PC1336, Cumulative Explained Ratio 98.28 Component PC1337, Cumulative Explained Ratio 98.28 Component PC1338, Cumulative Explained Ratio 98.29 Component PC1339, Cumulative Explained Ratio 98.3 Component PC1340, Cumulative Explained Ratio 98.31 Component PC1341, Cumulative Explained Ratio 98.32 Component PC1342, Cumulative Explained Ratio 98.32 Component PC1343, Cumulative Explained Ratio 98.33 Component PC1344, Cumulative Explained Ratio 98.34 Component PC1345, Cumulative Explained Ratio 98.35 Component PC1346, Cumulative Explained Ratio 98.35 Component PC1347, Cumulative Explained Ratio 98.36 Component PC1348, Cumulative Explained Ratio 98.37 Component PC1349, Cumulative Explained Ratio 98.38 Component PC1350, Cumulative Explained Ratio 98.38 Component PC1351, Cumulative Explained Ratio 98.39 Component PC1352, Cumulative Explained Ratio 98.4 Component PC1353, Cumulative Explained Ratio 98.41 Component PC1354, Cumulative Explained Ratio 98.41 Component PC1355, Cumulative Explained Ratio 98.42 Component PC1356, Cumulative Explained Ratio 98.43 Component PC1357, Cumulative Explained Ratio 98.44 Component PC1358, Cumulative Explained Ratio 98.44 Component PC1359, Cumulative Explained Ratio 98.45 Component PC1360, Cumulative Explained Ratio 98.46 Component PC1361, Cumulative Explained Ratio 98.47 Component PC1362, Cumulative Explained Ratio 98.47 Component PC1363, Cumulative Explained Ratio 98.48 Component PC1364, Cumulative Explained Ratio 98.49 Component PC1365, Cumulative Explained Ratio 98.49 Component PC1366, Cumulative Explained Ratio 98.5 Component PC1367, Cumulative Explained Ratio 98.51 Component PC1368, Cumulative Explained Ratio 98.51 Component PC1369, Cumulative Explained Ratio 98.52 Component PC1370, Cumulative Explained Ratio 98.53 Component PC1371, Cumulative Explained Ratio 98.54 Component PC1372, Cumulative Explained Ratio 98.54 Component PC1373, Cumulative Explained Ratio 98.55 Component PC1374, Cumulative Explained Ratio 98.56 Component PC1375, Cumulative Explained Ratio 98.56 Component PC1376, Cumulative Explained Ratio 98.57 Component PC1377, Cumulative Explained Ratio 98.58 Component PC1378, Cumulative Explained Ratio 98.58 Component PC1379, Cumulative Explained Ratio 98.59 Component PC1380, Cumulative Explained Ratio 98.6 Component PC1381, Cumulative Explained Ratio 98.6 Component PC1382, Cumulative Explained Ratio 98.61 Component PC1383, Cumulative Explained Ratio 98.62 Component PC1384, Cumulative Explained Ratio 98.62 Component PC1385, Cumulative Explained Ratio 98.63 Component PC1386, Cumulative Explained Ratio 98.64 Component PC1387, Cumulative Explained Ratio 98.64 Component PC1388, Cumulative Explained Ratio 98.65 Component PC1389, Cumulative Explained Ratio 98.65 Component PC1390, Cumulative Explained Ratio 98.66 Component PC1391, Cumulative Explained Ratio 98.67 Component PC1392, Cumulative Explained Ratio 98.67 Component PC1393, Cumulative Explained Ratio 98.68 Component PC1394, Cumulative Explained Ratio 98.69 Component PC1395, Cumulative Explained Ratio 98.69 Component PC1396, Cumulative Explained Ratio 98.7 Component PC1397, Cumulative Explained Ratio 98.7 Component PC1398, Cumulative Explained Ratio 98.71 Component PC1399, Cumulative Explained Ratio 98.72 Component PC1400, Cumulative Explained Ratio 98.72 Component PC1401, Cumulative Explained Ratio 98.73 Component PC1402, Cumulative Explained Ratio 98.73 Component PC1403, Cumulative Explained Ratio 98.74 Component PC1404, Cumulative Explained Ratio 98.75 Component PC1405, Cumulative Explained Ratio 98.75 Component PC1406, Cumulative Explained Ratio 98.76 Component PC1407, Cumulative Explained Ratio 98.76 Component PC1408, Cumulative Explained Ratio 98.77 Component PC1409, Cumulative Explained Ratio 98.78 Component PC1410, Cumulative Explained Ratio 98.78 Component PC1411, Cumulative Explained Ratio 98.79 Component PC1412, Cumulative Explained Ratio 98.79 Component PC1413, Cumulative Explained Ratio 98.8 Component PC1414, Cumulative Explained Ratio 98.81 Component PC1415, Cumulative Explained Ratio 98.81 Component PC1416, Cumulative Explained Ratio 98.82 Component PC1417, Cumulative Explained Ratio 98.82 Component PC1418, Cumulative Explained Ratio 98.83 Component PC1419, Cumulative Explained Ratio 98.83 Component PC1420, Cumulative Explained Ratio 98.84 Component PC1421, Cumulative Explained Ratio 98.84 Component PC1422, Cumulative Explained Ratio 98.85 Component PC1423, Cumulative Explained Ratio 98.86 Component PC1424, Cumulative Explained Ratio 98.86 Component PC1425, Cumulative Explained Ratio 98.87 Component PC1426, Cumulative Explained Ratio 98.87 Component PC1427, Cumulative Explained Ratio 98.88 Component PC1428, Cumulative Explained Ratio 98.88 Component PC1429, Cumulative Explained Ratio 98.89 Component PC1430, Cumulative Explained Ratio 98.89 Component PC1431, Cumulative Explained Ratio 98.9 Component PC1432, Cumulative Explained Ratio 98.9 Component PC1433, Cumulative Explained Ratio 98.91 Component PC1434, Cumulative Explained Ratio 98.91 Component PC1435, Cumulative Explained Ratio 98.92 Component PC1436, Cumulative Explained Ratio 98.93 Component PC1437, Cumulative Explained Ratio 98.93 Component PC1438, Cumulative Explained Ratio 98.94 Component PC1439, Cumulative Explained Ratio 98.94 Component PC1440, Cumulative Explained Ratio 98.95 Component PC1441, Cumulative Explained Ratio 98.95 Component PC1442, Cumulative Explained Ratio 98.96 Component PC1443, Cumulative Explained Ratio 98.96 Component PC1444, Cumulative Explained Ratio 98.97 Component PC1445, Cumulative Explained Ratio 98.97 Component PC1446, Cumulative Explained Ratio 98.98 Component PC1447, Cumulative Explained Ratio 98.98 Component PC1448, Cumulative Explained Ratio 98.99 Component PC1449, Cumulative Explained Ratio 98.99 Component PC1450, Cumulative Explained Ratio 99.0 Component PC1451, Cumulative Explained Ratio 99.0 Component PC1452, Cumulative Explained Ratio 99.01 Component PC1453, Cumulative Explained Ratio 99.01 Component PC1454, Cumulative Explained Ratio 99.02 Component PC1455, Cumulative Explained Ratio 99.02 Component PC1456, Cumulative Explained Ratio 99.02 Component PC1457, Cumulative Explained Ratio 99.03 Component PC1458, Cumulative Explained Ratio 99.03 Component PC1459, Cumulative Explained Ratio 99.04 Component PC1460, Cumulative Explained Ratio 99.04 Component PC1461, Cumulative Explained Ratio 99.05 Component PC1462, Cumulative Explained Ratio 99.05 Component PC1463, Cumulative Explained Ratio 99.06 Component PC1464, Cumulative Explained Ratio 99.06 Component PC1465, Cumulative Explained Ratio 99.07 Component PC1466, Cumulative Explained Ratio 99.07 Component PC1467, Cumulative Explained Ratio 99.08 Component PC1468, Cumulative Explained Ratio 99.08 Component PC1469, Cumulative Explained Ratio 99.09 Component PC1470, Cumulative Explained Ratio 99.09 Component PC1471, Cumulative Explained Ratio 99.09 Component PC1472, Cumulative Explained Ratio 99.1 Component PC1473, Cumulative Explained Ratio 99.1 Component PC1474, Cumulative Explained Ratio 99.11 Component PC1475, Cumulative Explained Ratio 99.11 Component PC1476, Cumulative Explained Ratio 99.12 Component PC1477, Cumulative Explained Ratio 99.12 Component PC1478, Cumulative Explained Ratio 99.13 Component PC1479, Cumulative Explained Ratio 99.13 Component PC1480, Cumulative Explained Ratio 99.13 Component PC1481, Cumulative Explained Ratio 99.14 Component PC1482, Cumulative Explained Ratio 99.14 Component PC1483, Cumulative Explained Ratio 99.15 Component PC1484, Cumulative Explained Ratio 99.15 Component PC1485, Cumulative Explained Ratio 99.16 Component PC1486, Cumulative Explained Ratio 99.16 Component PC1487, Cumulative Explained Ratio 99.16 Component PC1488, Cumulative Explained Ratio 99.17 Component PC1489, Cumulative Explained Ratio 99.17 Component PC1490, Cumulative Explained Ratio 99.18 Component PC1491, Cumulative Explained Ratio 99.18 Component PC1492, Cumulative Explained Ratio 99.18 Component PC1493, Cumulative Explained Ratio 99.19 Component PC1494, Cumulative Explained Ratio 99.19 Component PC1495, Cumulative Explained Ratio 99.2 Component PC1496, Cumulative Explained Ratio 99.2 Component PC1497, Cumulative Explained Ratio 99.2 Component PC1498, Cumulative Explained Ratio 99.21 Component PC1499, Cumulative Explained Ratio 99.21 Component PC1500, Cumulative Explained Ratio 99.22 Component PC1501, Cumulative Explained Ratio 99.22 Component PC1502, Cumulative Explained Ratio 99.22 Component PC1503, Cumulative Explained Ratio 99.23 Component PC1504, Cumulative Explained Ratio 99.23 Component PC1505, Cumulative Explained Ratio 99.24 Component PC1506, Cumulative Explained Ratio 99.24 Component PC1507, Cumulative Explained Ratio 99.24 Component PC1508, Cumulative Explained Ratio 99.25 Component PC1509, Cumulative Explained Ratio 99.25 Component PC1510, Cumulative Explained Ratio 99.26 Component PC1511, Cumulative Explained Ratio 99.26 Component PC1512, Cumulative Explained Ratio 99.26 Component PC1513, Cumulative Explained Ratio 99.27 Component PC1514, Cumulative Explained Ratio 99.27 Component PC1515, Cumulative Explained Ratio 99.27 Component PC1516, Cumulative Explained Ratio 99.28 Component PC1517, Cumulative Explained Ratio 99.28 Component PC1518, Cumulative Explained Ratio 99.29 Component PC1519, Cumulative Explained Ratio 99.29 Component PC1520, Cumulative Explained Ratio 99.29 Component PC1521, Cumulative Explained Ratio 99.3 Component PC1522, Cumulative Explained Ratio 99.3 Component PC1523, Cumulative Explained Ratio 99.3 Component PC1524, Cumulative Explained Ratio 99.31 Component PC1525, Cumulative Explained Ratio 99.31 Component PC1526, Cumulative Explained Ratio 99.31 Component PC1527, Cumulative Explained Ratio 99.32 Component PC1528, Cumulative Explained Ratio 99.32 Component PC1529, Cumulative Explained Ratio 99.33 Component PC1530, Cumulative Explained Ratio 99.33 Component PC1531, Cumulative Explained Ratio 99.33 Component PC1532, Cumulative Explained Ratio 99.34 Component PC1533, Cumulative Explained Ratio 99.34 Component PC1534, Cumulative Explained Ratio 99.34 Component PC1535, Cumulative Explained Ratio 99.35 Component PC1536, Cumulative Explained Ratio 99.35 Component PC1537, Cumulative Explained Ratio 99.35 Component PC1538, Cumulative Explained Ratio 99.36 Component PC1539, Cumulative Explained Ratio 99.36 Component PC1540, Cumulative Explained Ratio 99.36 Component PC1541, Cumulative Explained Ratio 99.37 Component PC1542, Cumulative Explained Ratio 99.37 Component PC1543, Cumulative Explained Ratio 99.37 Component PC1544, Cumulative Explained Ratio 99.38 Component PC1545, Cumulative Explained Ratio 99.38 Component PC1546, Cumulative Explained Ratio 99.38 Component PC1547, Cumulative Explained Ratio 99.39 Component PC1548, Cumulative Explained Ratio 99.39 Component PC1549, Cumulative Explained Ratio 99.39 Component PC1550, Cumulative Explained Ratio 99.4 Component PC1551, Cumulative Explained Ratio 99.4 Component PC1552, Cumulative Explained Ratio 99.4 Component PC1553, Cumulative Explained Ratio 99.41 Component PC1554, Cumulative Explained Ratio 99.41 Component PC1555, Cumulative Explained Ratio 99.41 Component PC1556, Cumulative Explained Ratio 99.42 Component PC1557, Cumulative Explained Ratio 99.42 Component PC1558, Cumulative Explained Ratio 99.42 Component PC1559, Cumulative Explained Ratio 99.43 Component PC1560, Cumulative Explained Ratio 99.43 Component PC1561, Cumulative Explained Ratio 99.43 Component PC1562, Cumulative Explained Ratio 99.43 Component PC1563, Cumulative Explained Ratio 99.44 Component PC1564, Cumulative Explained Ratio 99.44 Component PC1565, Cumulative Explained Ratio 99.44 Component PC1566, Cumulative Explained Ratio 99.45 Component PC1567, Cumulative Explained Ratio 99.45 Component PC1568, Cumulative Explained Ratio 99.45 Component PC1569, Cumulative Explained Ratio 99.46 Component PC1570, Cumulative Explained Ratio 99.46 Component PC1571, Cumulative Explained Ratio 99.46 Component PC1572, Cumulative Explained Ratio 99.47 Component PC1573, Cumulative Explained Ratio 99.47 Component PC1574, Cumulative Explained Ratio 99.47 Component PC1575, Cumulative Explained Ratio 99.47 Component PC1576, Cumulative Explained Ratio 99.48 Component PC1577, Cumulative Explained Ratio 99.48 Component PC1578, Cumulative Explained Ratio 99.48 Component PC1579, Cumulative Explained Ratio 99.49 Component PC1580, Cumulative Explained Ratio 99.49 Component PC1581, Cumulative Explained Ratio 99.49 Component PC1582, Cumulative Explained Ratio 99.49 Component PC1583, Cumulative Explained Ratio 99.5 Component PC1584, Cumulative Explained Ratio 99.5 Component PC1585, Cumulative Explained Ratio 99.5 Component PC1586, Cumulative Explained Ratio 99.51 Component PC1587, Cumulative Explained Ratio 99.51 Component PC1588, Cumulative Explained Ratio 99.51 Component PC1589, Cumulative Explained Ratio 99.51 Component PC1590, Cumulative Explained Ratio 99.52 Component PC1591, Cumulative Explained Ratio 99.52 Component PC1592, Cumulative Explained Ratio 99.52 Component PC1593, Cumulative Explained Ratio 99.53 Component PC1594, Cumulative Explained Ratio 99.53 Component PC1595, Cumulative Explained Ratio 99.53 Component PC1596, Cumulative Explained Ratio 99.53 Component PC1597, Cumulative Explained Ratio 99.54 Component PC1598, Cumulative Explained Ratio 99.54 Component PC1599, Cumulative Explained Ratio 99.54 Component PC1600, Cumulative Explained Ratio 99.55 Component PC1601, Cumulative Explained Ratio 99.55 Component PC1602, Cumulative Explained Ratio 99.55 Component PC1603, Cumulative Explained Ratio 99.55 Component PC1604, Cumulative Explained Ratio 99.56 Component PC1605, Cumulative Explained Ratio 99.56 Component PC1606, Cumulative Explained Ratio 99.56 Component PC1607, Cumulative Explained Ratio 99.56 Component PC1608, Cumulative Explained Ratio 99.57 Component PC1609, Cumulative Explained Ratio 99.57 Component PC1610, Cumulative Explained Ratio 99.57 Component PC1611, Cumulative Explained Ratio 99.57 Component PC1612, Cumulative Explained Ratio 99.58 Component PC1613, Cumulative Explained Ratio 99.58 Component PC1614, Cumulative Explained Ratio 99.58 Component PC1615, Cumulative Explained Ratio 99.59 Component PC1616, Cumulative Explained Ratio 99.59 Component PC1617, Cumulative Explained Ratio 99.59 Component PC1618, Cumulative Explained Ratio 99.59 Component PC1619, Cumulative Explained Ratio 99.6 Component PC1620, Cumulative Explained Ratio 99.6 Component PC1621, Cumulative Explained Ratio 99.6 Component PC1622, Cumulative Explained Ratio 99.6 Component PC1623, Cumulative Explained Ratio 99.61 Component PC1624, Cumulative Explained Ratio 99.61 Component PC1625, Cumulative Explained Ratio 99.61 Component PC1626, Cumulative Explained Ratio 99.61 Component PC1627, Cumulative Explained Ratio 99.62 Component PC1628, Cumulative Explained Ratio 99.62 Component PC1629, Cumulative Explained Ratio 99.62 Component PC1630, Cumulative Explained Ratio 99.62 Component PC1631, Cumulative Explained Ratio 99.63 Component PC1632, Cumulative Explained Ratio 99.63 Component PC1633, Cumulative Explained Ratio 99.63 Component PC1634, Cumulative Explained Ratio 99.63 Component PC1635, Cumulative Explained Ratio 99.64 Component PC1636, Cumulative Explained Ratio 99.64 Component PC1637, Cumulative Explained Ratio 99.64 Component PC1638, Cumulative Explained Ratio 99.64 Component PC1639, Cumulative Explained Ratio 99.64 Component PC1640, Cumulative Explained Ratio 99.65 Component PC1641, Cumulative Explained Ratio 99.65 Component PC1642, Cumulative Explained Ratio 99.65 Component PC1643, Cumulative Explained Ratio 99.65 Component PC1644, Cumulative Explained Ratio 99.66 Component PC1645, Cumulative Explained Ratio 99.66 Component PC1646, Cumulative Explained Ratio 99.66 Component PC1647, Cumulative Explained Ratio 99.66 Component PC1648, Cumulative Explained Ratio 99.67 Component PC1649, Cumulative Explained Ratio 99.67 Component PC1650, Cumulative Explained Ratio 99.67 Component PC1651, Cumulative Explained Ratio 99.67 Component PC1652, Cumulative Explained Ratio 99.68 Component PC1653, Cumulative Explained Ratio 99.68 Component PC1654, Cumulative Explained Ratio 99.68 Component PC1655, Cumulative Explained Ratio 99.68 Component PC1656, Cumulative Explained Ratio 99.68 Component PC1657, Cumulative Explained Ratio 99.69 Component PC1658, Cumulative Explained Ratio 99.69 Component PC1659, Cumulative Explained Ratio 99.69 Component PC1660, Cumulative Explained Ratio 99.69 Component PC1661, Cumulative Explained Ratio 99.7 Component PC1662, Cumulative Explained Ratio 99.7 Component PC1663, Cumulative Explained Ratio 99.7 Component PC1664, Cumulative Explained Ratio 99.7 Component PC1665, Cumulative Explained Ratio 99.7 Component PC1666, Cumulative Explained Ratio 99.71 Component PC1667, Cumulative Explained Ratio 99.71 Component PC1668, Cumulative Explained Ratio 99.71 Component PC1669, Cumulative Explained Ratio 99.71 Component PC1670, Cumulative Explained Ratio 99.71 Component PC1671, Cumulative Explained Ratio 99.72 Component PC1672, Cumulative Explained Ratio 99.72 Component PC1673, Cumulative Explained Ratio 99.72 Component PC1674, Cumulative Explained Ratio 99.72 Component PC1675, Cumulative Explained Ratio 99.73 Component PC1676, Cumulative Explained Ratio 99.73 Component PC1677, Cumulative Explained Ratio 99.73 Component PC1678, Cumulative Explained Ratio 99.73 Component PC1679, Cumulative Explained Ratio 99.73 Component PC1680, Cumulative Explained Ratio 99.74 Component PC1681, Cumulative Explained Ratio 99.74 Component PC1682, Cumulative Explained Ratio 99.74 Component PC1683, Cumulative Explained Ratio 99.74 Component PC1684, Cumulative Explained Ratio 99.74 Component PC1685, Cumulative Explained Ratio 99.74 Component PC1686, Cumulative Explained Ratio 99.75 Component PC1687, Cumulative Explained Ratio 99.75 Component PC1688, Cumulative Explained Ratio 99.75 Component PC1689, Cumulative Explained Ratio 99.75 Component PC1690, Cumulative Explained Ratio 99.75 Component PC1691, Cumulative Explained Ratio 99.76 Component PC1692, Cumulative Explained Ratio 99.76 Component PC1693, Cumulative Explained Ratio 99.76 Component PC1694, Cumulative Explained Ratio 99.76 Component PC1695, Cumulative Explained Ratio 99.76 Component PC1696, Cumulative Explained Ratio 99.77 Component PC1697, Cumulative Explained Ratio 99.77 Component PC1698, Cumulative Explained Ratio 99.77 Component PC1699, Cumulative Explained Ratio 99.77 Component PC1700, Cumulative Explained Ratio 99.77 Component PC1701, Cumulative Explained Ratio 99.78 Component PC1702, Cumulative Explained Ratio 99.78 Component PC1703, Cumulative Explained Ratio 99.78 Component PC1704, Cumulative Explained Ratio 99.78 Component PC1705, Cumulative Explained Ratio 99.78 Component PC1706, Cumulative Explained Ratio 99.78 Component PC1707, Cumulative Explained Ratio 99.79 Component PC1708, Cumulative Explained Ratio 99.79 Component PC1709, Cumulative Explained Ratio 99.79 Component PC1710, Cumulative Explained Ratio 99.79 Component PC1711, Cumulative Explained Ratio 99.79 Component PC1712, Cumulative Explained Ratio 99.8 Component PC1713, Cumulative Explained Ratio 99.8 Component PC1714, Cumulative Explained Ratio 99.8 Component PC1715, Cumulative Explained Ratio 99.8 Component PC1716, Cumulative Explained Ratio 99.8 Component PC1717, Cumulative Explained Ratio 99.8 Component PC1718, Cumulative Explained Ratio 99.81 Component PC1719, Cumulative Explained Ratio 99.81 Component PC1720, Cumulative Explained Ratio 99.81 Component PC1721, Cumulative Explained Ratio 99.81 Component PC1722, Cumulative Explained Ratio 99.81 Component PC1723, Cumulative Explained Ratio 99.81 Component PC1724, Cumulative Explained Ratio 99.82 Component PC1725, Cumulative Explained Ratio 99.82 Component PC1726, Cumulative Explained Ratio 99.82 Component PC1727, Cumulative Explained Ratio 99.82 Component PC1728, Cumulative Explained Ratio 99.82 Component PC1729, Cumulative Explained Ratio 99.82 Component PC1730, Cumulative Explained Ratio 99.83 Component PC1731, Cumulative Explained Ratio 99.83 Component PC1732, Cumulative Explained Ratio 99.83 Component PC1733, Cumulative Explained Ratio 99.83 Component PC1734, Cumulative Explained Ratio 99.83 Component PC1735, Cumulative Explained Ratio 99.83 Component PC1736, Cumulative Explained Ratio 99.83 Component PC1737, Cumulative Explained Ratio 99.84 Component PC1738, Cumulative Explained Ratio 99.84 Component PC1739, Cumulative Explained Ratio 99.84 Component PC1740, Cumulative Explained Ratio 99.84 Component PC1741, Cumulative Explained Ratio 99.84 Component PC1742, Cumulative Explained Ratio 99.84 Component PC1743, Cumulative Explained Ratio 99.85 Component PC1744, Cumulative Explained Ratio 99.85 Component PC1745, Cumulative Explained Ratio 99.85 Component PC1746, Cumulative Explained Ratio 99.85 Component PC1747, Cumulative Explained Ratio 99.85 Component PC1748, Cumulative Explained Ratio 99.85 Component PC1749, Cumulative Explained Ratio 99.85 Component PC1750, Cumulative Explained Ratio 99.86 Component PC1751, Cumulative Explained Ratio 99.86 Component PC1752, Cumulative Explained Ratio 99.86 Component PC1753, Cumulative Explained Ratio 99.86 Component PC1754, Cumulative Explained Ratio 99.86 Component PC1755, Cumulative Explained Ratio 99.86 Component PC1756, Cumulative Explained Ratio 99.86 Component PC1757, Cumulative Explained Ratio 99.87 Component PC1758, Cumulative Explained Ratio 99.87 Component PC1759, Cumulative Explained Ratio 99.87 Component PC1760, Cumulative Explained Ratio 99.87 Component PC1761, Cumulative Explained Ratio 99.87 Component PC1762, Cumulative Explained Ratio 99.87 Component PC1763, Cumulative Explained Ratio 99.87 Component PC1764, Cumulative Explained Ratio 99.88 Component PC1765, Cumulative Explained Ratio 99.88 Component PC1766, Cumulative Explained Ratio 99.88 Component PC1767, Cumulative Explained Ratio 99.88 Component PC1768, Cumulative Explained Ratio 99.88 Component PC1769, Cumulative Explained Ratio 99.88 Component PC1770, Cumulative Explained Ratio 99.88 Component PC1771, Cumulative Explained Ratio 99.88 Component PC1772, Cumulative Explained Ratio 99.89 Component PC1773, Cumulative Explained Ratio 99.89 Component PC1774, Cumulative Explained Ratio 99.89 Component PC1775, Cumulative Explained Ratio 99.89 Component PC1776, Cumulative Explained Ratio 99.89 Component PC1777, Cumulative Explained Ratio 99.89 Component PC1778, Cumulative Explained Ratio 99.89 Component PC1779, Cumulative Explained Ratio 99.89 Component PC1780, Cumulative Explained Ratio 99.9 Component PC1781, Cumulative Explained Ratio 99.9 Component PC1782, Cumulative Explained Ratio 99.9 Component PC1783, Cumulative Explained Ratio 99.9 Component PC1784, Cumulative Explained Ratio 99.9 Component PC1785, Cumulative Explained Ratio 99.9 Component PC1786, Cumulative Explained Ratio 99.9 Component PC1787, Cumulative Explained Ratio 99.9 Component PC1788, Cumulative Explained Ratio 99.91 Component PC1789, Cumulative Explained Ratio 99.91 Component PC1790, Cumulative Explained Ratio 99.91 Component PC1791, Cumulative Explained Ratio 99.91 Component PC1792, Cumulative Explained Ratio 99.91 Component PC1793, Cumulative Explained Ratio 99.91 Component PC1794, Cumulative Explained Ratio 99.91 Component PC1795, Cumulative Explained Ratio 99.91 Component PC1796, Cumulative Explained Ratio 99.91 Component PC1797, Cumulative Explained Ratio 99.92 Component PC1798, Cumulative Explained Ratio 99.92 Component PC1799, Cumulative Explained Ratio 99.92 Component PC1800, Cumulative Explained Ratio 99.92 Component PC1801, Cumulative Explained Ratio 99.92 Component PC1802, Cumulative Explained Ratio 99.92 Component PC1803, Cumulative Explained Ratio 99.92 Component PC1804, Cumulative Explained Ratio 99.92 Component PC1805, Cumulative Explained Ratio 99.92 Component PC1806, Cumulative Explained Ratio 99.92 Component PC1807, Cumulative Explained Ratio 99.93 Component PC1808, Cumulative Explained Ratio 99.93 Component PC1809, Cumulative Explained Ratio 99.93 Component PC1810, Cumulative Explained Ratio 99.93 Component PC1811, Cumulative Explained Ratio 99.93 Component PC1812, Cumulative Explained Ratio 99.93 Component PC1813, Cumulative Explained Ratio 99.93 Component PC1814, Cumulative Explained Ratio 99.93 Component PC1815, Cumulative Explained Ratio 99.93 Component PC1816, Cumulative Explained Ratio 99.93 Component PC1817, Cumulative Explained Ratio 99.94 Component PC1818, Cumulative Explained Ratio 99.94 Component PC1819, Cumulative Explained Ratio 99.94 Component PC1820, Cumulative Explained Ratio 99.94 Component PC1821, Cumulative Explained Ratio 99.94 Component PC1822, Cumulative Explained Ratio 99.94 Component PC1823, Cumulative Explained Ratio 99.94 Component PC1824, Cumulative Explained Ratio 99.94 Component PC1825, Cumulative Explained Ratio 99.94 Component PC1826, Cumulative Explained Ratio 99.94 Component PC1827, Cumulative Explained Ratio 99.94 Component PC1828, Cumulative Explained Ratio 99.95 Component PC1829, Cumulative Explained Ratio 99.95 Component PC1830, Cumulative Explained Ratio 99.95 Component PC1831, Cumulative Explained Ratio 99.95 Component PC1832, Cumulative Explained Ratio 99.95 Component PC1833, Cumulative Explained Ratio 99.95 Component PC1834, Cumulative Explained Ratio 99.95 Component PC1835, Cumulative Explained Ratio 99.95 Component PC1836, Cumulative Explained Ratio 99.95 Component PC1837, Cumulative Explained Ratio 99.95 Component PC1838, Cumulative Explained Ratio 99.95 Component PC1839, Cumulative Explained Ratio 99.95 Component PC1840, Cumulative Explained Ratio 99.95 Component PC1841, Cumulative Explained Ratio 99.96 Component PC1842, Cumulative Explained Ratio 99.96 Component PC1843, Cumulative Explained Ratio 99.96 Component PC1844, Cumulative Explained Ratio 99.96 Component PC1845, Cumulative Explained Ratio 99.96 Component PC1846, Cumulative Explained Ratio 99.96 Component PC1847, Cumulative Explained Ratio 99.96 Component PC1848, Cumulative Explained Ratio 99.96 Component PC1849, Cumulative Explained Ratio 99.96 Component PC1850, Cumulative Explained Ratio 99.96 Component PC1851, Cumulative Explained Ratio 99.96 Component PC1852, Cumulative Explained Ratio 99.96 Component PC1853, Cumulative Explained Ratio 99.96 Component PC1854, Cumulative Explained Ratio 99.96 Component PC1855, Cumulative Explained Ratio 99.96 Component PC1856, Cumulative Explained Ratio 99.96 Component PC1857, Cumulative Explained Ratio 99.97 Component PC1858, Cumulative Explained Ratio 99.97 Component PC1859, Cumulative Explained Ratio 99.97 Component PC1860, Cumulative Explained Ratio 99.97 Component PC1861, Cumulative Explained Ratio 99.97 Component PC1862, Cumulative Explained Ratio 99.97 Component PC1863, Cumulative Explained Ratio 99.97 Component PC1864, Cumulative Explained Ratio 99.97 Component PC1865, Cumulative Explained Ratio 99.97 Component PC1866, Cumulative Explained Ratio 99.97 Component PC1867, Cumulative Explained Ratio 99.97 Component PC1868, Cumulative Explained Ratio 99.97 Component PC1869, Cumulative Explained Ratio 99.97 Component PC1870, Cumulative Explained Ratio 99.97 Component PC1871, Cumulative Explained Ratio 99.97 Component PC1872, Cumulative Explained Ratio 99.97 Component PC1873, Cumulative Explained Ratio 99.97 Component PC1874, Cumulative Explained Ratio 99.97 Component PC1875, Cumulative Explained Ratio 99.98 Component PC1876, Cumulative Explained Ratio 99.98 Component PC1877, Cumulative Explained Ratio 99.98 Component PC1878, Cumulative Explained Ratio 99.98 Component PC1879, Cumulative Explained Ratio 99.98 Component PC1880, Cumulative Explained Ratio 99.98 Component PC1881, Cumulative Explained Ratio 99.98 Component PC1882, Cumulative Explained Ratio 99.98 Component PC1883, Cumulative Explained Ratio 99.98 Component PC1884, Cumulative Explained Ratio 99.98 Component PC1885, Cumulative Explained Ratio 99.98 Component PC1886, Cumulative Explained Ratio 99.98 Component PC1887, Cumulative Explained Ratio 99.98 Component PC1888, Cumulative Explained Ratio 99.98 Component PC1889, Cumulative Explained Ratio 99.98 Component PC1890, Cumulative Explained Ratio 99.98 Component PC1891, Cumulative Explained Ratio 99.98 Component PC1892, Cumulative Explained Ratio 99.98 Component PC1893, Cumulative Explained Ratio 99.98 Component PC1894, Cumulative Explained Ratio 99.98 Component PC1895, Cumulative Explained Ratio 99.98 Component PC1896, Cumulative Explained Ratio 99.98 Component PC1897, Cumulative Explained Ratio 99.98 Component PC1898, Cumulative Explained Ratio 99.99 Component PC1899, Cumulative Explained Ratio 99.99 Component PC1900, Cumulative Explained Ratio 99.99 Component PC1901, Cumulative Explained Ratio 99.99 Component PC1902, Cumulative Explained Ratio 99.99 Component PC1903, Cumulative Explained Ratio 99.99 Component PC1904, Cumulative Explained Ratio 99.99 Component PC1905, Cumulative Explained Ratio 99.99 Component PC1906, Cumulative Explained Ratio 99.99 Component PC1907, Cumulative Explained Ratio 99.99 Component PC1908, Cumulative Explained Ratio 99.99 Component PC1909, Cumulative Explained Ratio 99.99 Component PC1910, Cumulative Explained Ratio 99.99 Component PC1911, Cumulative Explained Ratio 99.99 Component PC1912, Cumulative Explained Ratio 99.99 Component PC1913, Cumulative Explained Ratio 99.99 Component PC1914, Cumulative Explained Ratio 99.99 Component PC1915, Cumulative Explained Ratio 99.99 Component PC1916, Cumulative Explained Ratio 99.99 Component PC1917, Cumulative Explained Ratio 99.99 Component PC1918, Cumulative Explained Ratio 99.99 Component PC1919, Cumulative Explained Ratio 99.99 Component PC1920, Cumulative Explained Ratio 99.99 Component PC1921, Cumulative Explained Ratio 99.99 Component PC1922, Cumulative Explained Ratio 99.99 Component PC1923, Cumulative Explained Ratio 99.99 Component PC1924, Cumulative Explained Ratio 99.99 Component PC1925, Cumulative Explained Ratio 99.99 Component PC1926, Cumulative Explained Ratio 99.99 Component PC1927, Cumulative Explained Ratio 100.0 Component PC1928, Cumulative Explained Ratio 100.0 Component PC1929, Cumulative Explained Ratio 100.0 Component PC1930, Cumulative Explained Ratio 100.0 Component PC1931, Cumulative Explained Ratio 100.0 Component PC1932, Cumulative Explained Ratio 100.0 Component PC1933, Cumulative Explained Ratio 100.0 Component PC1934, Cumulative Explained Ratio 100.0 Component PC1935, Cumulative Explained Ratio 100.0 Component PC1936, Cumulative Explained Ratio 100.0 Component PC1937, Cumulative Explained Ratio 100.0 Component PC1938, Cumulative Explained Ratio 100.0 Component PC1939, Cumulative Explained Ratio 100.0 Component PC1940, Cumulative Explained Ratio 100.0 Component PC1941, Cumulative Explained Ratio 100.0 Component PC1942, Cumulative Explained Ratio 100.0 Component PC1943, Cumulative Explained Ratio 100.0 Component PC1944, Cumulative Explained Ratio 100.0 Component PC1945, Cumulative Explained Ratio 100.0 Component PC1946, Cumulative Explained Ratio 100.0 Component PC1947, Cumulative Explained Ratio 100.0 Component PC1948, Cumulative Explained Ratio 100.0 Component PC1949, Cumulative Explained Ratio 100.0 Component PC1950, Cumulative Explained Ratio 100.0 Component PC1951, Cumulative Explained Ratio 100.0 Component PC1952, Cumulative Explained Ratio 100.0 Component PC1953, Cumulative Explained Ratio 100.0 Component PC1954, Cumulative Explained Ratio 100.0 Component PC1955, Cumulative Explained Ratio 100.0 Component PC1956, Cumulative Explained Ratio 100.0 Component PC1957, Cumulative Explained Ratio 100.0 Component PC1958, Cumulative Explained Ratio 100.0 Component PC1959, Cumulative Explained Ratio 100.0 Component PC1960, Cumulative Explained Ratio 100.0 Component PC1961, Cumulative Explained Ratio 100.0 Component PC1962, Cumulative Explained Ratio 100.0 Component PC1963, Cumulative Explained Ratio 100.0 Component PC1964, Cumulative Explained Ratio 100.0 Component PC1965, Cumulative Explained Ratio 100.0 Component PC1966, Cumulative Explained Ratio 100.0 Component PC1967, Cumulative Explained Ratio 100.0 Component PC1968, Cumulative Explained Ratio 100.0 Component PC1969, Cumulative Explained Ratio 100.0 Component PC1970, Cumulative Explained Ratio 100.0 Component PC1971, Cumulative Explained Ratio 100.0 Component PC1972, Cumulative Explained Ratio 100.0 Component PC1973, Cumulative Explained Ratio 100.0 Component PC1974, Cumulative Explained Ratio 100.0 Component PC1975, Cumulative Explained Ratio 100.0 Component PC1976, Cumulative Explained Ratio 100.0 Component PC1977, Cumulative Explained Ratio 100.0 Component PC1978, Cumulative Explained Ratio 100.0 Component PC1979, Cumulative Explained Ratio 100.0 Component PC1980, Cumulative Explained Ratio 100.0 Component PC1981, Cumulative Explained Ratio 100.0 Component PC1982, Cumulative Explained Ratio 100.0 Component PC1983, Cumulative Explained Ratio 100.0 Component PC1984, Cumulative Explained Ratio 100.0 Component PC1985, Cumulative Explained Ratio 100.0 Component PC1986, Cumulative Explained Ratio 100.0 Component PC1987, Cumulative Explained Ratio 100.0 Component PC1988, Cumulative Explained Ratio 100.0 Component PC1989, Cumulative Explained Ratio 100.0 Component PC1990, Cumulative Explained Ratio 100.0 Component PC1991, Cumulative Explained Ratio 100.0 Component PC1992, Cumulative Explained Ratio 100.0 Component PC1993, Cumulative Explained Ratio 100.0 Component PC1994, Cumulative Explained Ratio 100.0 Component PC1995, Cumulative Explained Ratio 100.0 Component PC1996, Cumulative Explained Ratio 100.0 Component PC1997, Cumulative Explained Ratio 100.0 Component PC1998, Cumulative Explained Ratio 100.0 Component PC1999, Cumulative Explained Ratio 100.0 Component PC2000, Cumulative Explained Ratio 100.0 Component PC2001, Cumulative Explained Ratio 100.0 Component PC2002, Cumulative Explained Ratio 100.0 Component PC2003, Cumulative Explained Ratio 100.0 Component PC2004, Cumulative Explained Ratio 100.0 Component PC2005, Cumulative Explained Ratio 100.0 Component PC2006, Cumulative Explained Ratio 100.0 Component PC2007, Cumulative Explained Ratio 100.0 Component PC2008, Cumulative Explained Ratio 100.0 Component PC2009, Cumulative Explained Ratio 100.0 Component PC2010, Cumulative Explained Ratio 100.0 Component PC2011, Cumulative Explained Ratio 100.0 Component PC2012, Cumulative Explained Ratio 100.0 Component PC2013, Cumulative Explained Ratio 100.0 Component PC2014, Cumulative Explained Ratio 100.0 Component PC2015, Cumulative Explained Ratio 100.0 Component PC2016, Cumulative Explained Ratio 100.0 Component PC2017, Cumulative Explained Ratio 100.0 Component PC2018, Cumulative Explained Ratio 100.0 Component PC2019, Cumulative Explained Ratio 100.0 Component PC2020, Cumulative Explained Ratio 100.0 Component PC2021, Cumulative Explained Ratio 100.0 Component PC2022, Cumulative Explained Ratio 100.0 Component PC2023, Cumulative Explained Ratio 100.0 Component PC2024, Cumulative Explained Ratio 100.0 Component PC2025, Cumulative Explained Ratio 100.0 Component PC2026, Cumulative Explained Ratio 100.0 Component PC2027, Cumulative Explained Ratio 100.0 Component PC2028, Cumulative Explained Ratio 100.0 Component PC2029, Cumulative Explained Ratio 100.0 Component PC2030, Cumulative Explained Ratio 100.0 Component PC2031, Cumulative Explained Ratio 100.0 Component PC2032, Cumulative Explained Ratio 100.0 Component PC2033, Cumulative Explained Ratio 100.0 Component PC2034, Cumulative Explained Ratio 100.0 Component PC2035, Cumulative Explained Ratio 100.0 Component PC2036, Cumulative Explained Ratio 100.0 Component PC2037, Cumulative Explained Ratio 100.0 Component PC2038, Cumulative Explained Ratio 100.0 Component PC2039, Cumulative Explained Ratio 100.0 Component PC2040, Cumulative Explained Ratio 100.0 Component PC2041, Cumulative Explained Ratio 100.0 Component PC2042, Cumulative Explained Ratio 100.0 Component PC2043, Cumulative Explained Ratio 100.0 Component PC2044, Cumulative Explained Ratio 100.0 Component PC2045, Cumulative Explained Ratio 100.0 Component PC2046, Cumulative Explained Ratio 100.0 Component PC2047, Cumulative Explained Ratio 100.0 Component PC2048, Cumulative Explained Ratio 100.0 Component PC2049, Cumulative Explained Ratio 100.0 Component PC2050, Cumulative Explained Ratio 100.0 Component PC2051, Cumulative Explained Ratio 100.0 Component PC2052, Cumulative Explained Ratio 100.0 Component PC2053, Cumulative Explained Ratio 100.0 Component PC2054, Cumulative Explained Ratio 100.0 Component PC2055, Cumulative Explained Ratio 100.0 Component PC2056, Cumulative Explained Ratio 100.0 Component PC2057, Cumulative Explained Ratio 100.0 Component PC2058, Cumulative Explained Ratio 100.0 Component PC2059, Cumulative Explained Ratio 100.0 Component PC2060, Cumulative Explained Ratio 100.0 List of most relevant features: ['N_ADATE_16', 'RFA_16_', 'N_ADATE_5', 'RFA_5_', 'N_ADATE_12', 'RFA_12_', 'N_ADATE_10', 'RFA_10_', 'N_ADATE_13', 'RFA_13_', 'N_ADATE_11', 'RFA_11_', 'RFA_8_', 'N_ADATE_8', 'N_ADATE_7', 'RFA_7_', 'RFA_15_', 'N_ADATE_15', 'N_ADATE_3', 'RFA_3_', 'N_ADATE_4', 'N_ADATE_20', 'RFA_20_', 'RFA_17_', 'N_ADATE_17', 'RFA_6_', 'N_ADATE_6', 'RFA_21_', 'N_ADATE_21', 'N_ADATE_23', 'RFA_23_', 'RFA_24_', 'N_ADATE_24', 'N_ADATE_18', 'RFA_18_', 'N_ADATE_14', 'RFA_14_', 'RFA_9_', 'N_ADATE_9', 'N_ADATE_19', 'RFA_19_', 'N_ADATE_22', 'RFA_22_']
dic['df_corr0'] #RFA (RECENCY-FREQUENCY-DONATION AMOUNT)
| PC0 | PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | PC11 | PC12 | PC13 | PC14 | PC15 | PC16 | PC17 | PC18 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MDMAUD_A_C | 0.018042 | 0.015456 | -0.149064 | -0.019236 | 0.007594 | 0.018477 | -0.154734 | 0.116098 | 0.114025 | -0.073732 | -0.019163 | 0.017721 | -0.031161 | -0.015861 | -0.016299 | 0.014599 | -0.018131 | 0.020099 | -0.016793 |
| MDMAUD_A_L | 0.001589 | 0.008810 | -0.229770 | 0.005101 | 0.019925 | 0.003274 | 0.383191 | -0.199470 | -0.188159 | 0.247387 | -0.008310 | 0.001474 | -0.006537 | -0.001788 | -0.002731 | 0.001129 | -0.000763 | -0.005698 | -0.003575 |
| MDMAUD_A_M | 0.005669 | 0.002991 | 0.571367 | -0.006122 | 0.002722 | 0.006084 | 0.065440 | -0.406605 | -0.384251 | -0.120447 | 0.003699 | 0.005693 | 0.030887 | -0.005917 | -0.003685 | 0.005794 | -0.005423 | 0.006407 | -0.006104 |
| MDMAUD_A_T | 0.004840 | 0.000002 | 0.497756 | 0.003138 | 0.029318 | 0.004777 | 0.027111 | 0.307243 | 0.385606 | 0.068571 | 0.003095 | 0.004883 | 0.034797 | -0.006901 | -0.006118 | 0.004836 | -0.005722 | 0.010998 | -0.003799 |
| MDMAUD_A_X | -0.019031 | -0.017436 | 0.000011 | 0.017259 | -0.017236 | -0.020003 | 0.013368 | 0.006385 | -0.010727 | 0.016588 | 0.018691 | -0.018715 | 0.018495 | 0.017418 | 0.017453 | -0.015766 | 0.018936 | -0.019835 | 0.018416 |
| MDMAUD_F_1 | 0.017493 | 0.011716 | -0.367659 | -0.011385 | 0.029760 | 0.018247 | -0.103744 | -0.073156 | -0.005357 | -0.111649 | -0.026309 | 0.017163 | 0.006150 | -0.016253 | -0.014260 | 0.014447 | -0.017101 | 0.016342 | -0.017288 |
| MDMAUD_F_2 | 0.009134 | 0.010745 | 0.198359 | -0.017963 | -0.020640 | 0.009672 | 0.149237 | 0.132535 | 0.033564 | 0.154743 | 0.004546 | 0.009087 | -0.016142 | -0.007180 | -0.013142 | 0.007840 | -0.009476 | 0.008583 | -0.008502 |
| MDMAUD_F_5 | 0.000074 | 0.008839 | 0.757771 | 0.006840 | 0.018940 | 0.000373 | -0.047770 | -0.081978 | -0.013490 | -0.047329 | -0.000346 | -0.000032 | -0.059401 | -0.001895 | 0.004711 | -0.000400 | -0.000205 | 0.008320 | 0.000355 |
| MDMAUD_F_X | -0.019031 | -0.017436 | 0.000011 | 0.017259 | -0.017236 | -0.020003 | 0.013368 | 0.006385 | -0.010727 | 0.016588 | 0.018691 | -0.018715 | 0.018495 | 0.017418 | 0.017453 | -0.015766 | 0.018936 | -0.019835 | 0.018416 |
| MDMAUD_R_C | 0.011964 | 0.010372 | -0.144579 | -0.011570 | 0.008184 | 0.013933 | 0.138831 | -0.485220 | 0.416062 | -0.066258 | -0.007584 | 0.011789 | -0.016661 | -0.011759 | -0.007504 | 0.011279 | -0.013252 | 0.014266 | -0.009293 |
| MDMAUD_R_D | 0.011873 | 0.005325 | 0.572235 | -0.015847 | -0.003128 | 0.012053 | -0.036160 | 0.166282 | -0.061103 | 0.050787 | -0.033787 | 0.011536 | 0.003412 | -0.010497 | -0.007204 | 0.010207 | -0.011222 | 0.016303 | -0.012641 |
| MDMAUD_R_I | 0.003463 | 0.011567 | -0.167709 | 0.000825 | 0.011966 | 0.002468 | -0.488888 | -0.060757 | -0.211608 | 0.176927 | 0.006366 | 0.003455 | -0.003286 | -0.002155 | -0.006740 | 0.001909 | -0.003240 | 0.002206 | -0.005699 |
| MDMAUD_R_L | 0.009652 | 0.007848 | -0.234671 | -0.006241 | 0.018204 | 0.009839 | 0.250699 | 0.494720 | -0.266864 | -0.151971 | -0.001409 | 0.009556 | -0.017742 | -0.009037 | -0.013843 | 0.006709 | -0.008642 | 0.005105 | -0.009105 |
| MDMAUD_R_X | -0.019031 | -0.017436 | 0.000011 | 0.017259 | -0.017236 | -0.020003 | 0.013368 | 0.006385 | -0.010727 | 0.016588 | 0.018691 | -0.018715 | 0.018495 | 0.017418 | 0.017453 | -0.015766 | 0.018936 | -0.019835 | 0.018416 |
| RFA_2A_D | -0.449944 | 0.449445 | 0.025572 | 0.453980 | -0.453583 | -0.479318 | 0.338141 | 0.172674 | -0.252580 | 0.392017 | 0.446365 | -0.447049 | 0.444188 | 0.450398 | 0.447280 | -0.448959 | 0.448141 | -0.446388 | 0.449141 |
| RFA_2A_E | -0.310382 | 0.309198 | 0.019075 | 0.300412 | -0.300383 | -0.265401 | 0.199128 | 0.137925 | -0.185495 | 0.271149 | 0.308544 | -0.308767 | 0.306581 | 0.310254 | 0.312032 | -0.310482 | 0.310864 | -0.310034 | 0.310391 |
| RFA_2A_F | 0.348883 | -0.352199 | -0.014224 | -0.324822 | 0.324594 | 0.347060 | -0.240807 | -0.130334 | 0.201022 | -0.305758 | -0.346590 | 0.347082 | -0.344230 | -0.348391 | -0.349850 | 0.347981 | -0.348949 | 0.345405 | -0.348125 |
| RFA_2A_G | 0.169729 | -0.164088 | -0.018068 | -0.191668 | 0.191674 | 0.143598 | -0.118626 | -0.089039 | 0.100552 | -0.146416 | -0.168436 | 0.168484 | -0.167968 | -0.170488 | -0.168588 | 0.170336 | -0.169027 | 0.171462 | -0.170176 |
| RFA_2F | -1.000000 | 0.999345 | 0.057296 | 0.999485 | -0.998440 | -0.998539 | 0.715155 | 0.401758 | -0.583938 | 0.883298 | 0.999152 | -0.999993 | 0.990182 | 0.999993 | 0.999924 | -0.999992 | 0.999996 | -0.999908 | 0.999989 |
#dic['df_corr2'] #DEMOGRAPHICS
dic['df_corr3'] #DONOR INTERESTS
| PC0 | PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | PC11 | PC12 | PC13 | PC14 | PC15 | PC16 | PC17 | PC18 | PC19 | PC20 | PC21 | PC22 | PC23 | PC24 | PC25 | PC26 | PC27 | PC28 | PC29 | PC30 | PC31 | PC32 | PC33 | PC34 | PC35 | PC36 | PC37 | PC38 | PC39 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BIBLE_ | -0.468784 | -0.175513 | 0.353935 | 0.250161 | 0.197781 | -0.186505 | -0.248671 | 0.185927 | 0.021958 | -0.409807 | 0.082381 | 0.418516 | -0.091726 | 0.043845 | -0.128833 | -0.015284 | 0.074872 | 0.004011 | -0.016403 | -0.075336 | -0.046664 | 0.127956 | -0.322555 | -0.395662 | 0.426533 | 0.079977 | -0.044698 | -0.110238 | -0.093846 | 0.214875 | 0.282086 | 0.090861 | -0.224089 | -0.505104 | -0.264307 | 0.070398 | 0.373057 | -0.220216 | 0.747488 | 0.059306 |
| BIBLE_Y | 0.468784 | 0.175513 | -0.353935 | -0.250161 | -0.197781 | 0.186505 | 0.248671 | -0.185927 | -0.021958 | 0.409807 | -0.082381 | -0.418516 | 0.091726 | -0.043845 | 0.128833 | 0.015284 | -0.074872 | -0.004011 | 0.016403 | 0.075336 | 0.046664 | -0.127956 | 0.322555 | 0.395662 | -0.426533 | -0.079977 | 0.044698 | 0.110238 | 0.093846 | -0.214875 | -0.282086 | -0.090861 | 0.224089 | 0.505104 | 0.264307 | -0.070398 | -0.373057 | 0.220216 | -0.747488 | -0.059306 |
| BOATS_ | -0.301620 | 0.107099 | 0.105711 | -0.545237 | -0.484858 | 0.052243 | -0.170582 | 0.137156 | -0.032473 | -0.212780 | 0.062768 | 0.003365 | 0.133932 | -0.410728 | -0.091531 | -0.161115 | 0.135389 | 0.110619 | 0.037867 | 0.008389 | 0.006893 | 0.121909 | -0.027894 | 0.073832 | -0.098680 | 0.465161 | 0.079639 | -0.336208 | -0.098350 | -0.131510 | -0.061335 | 0.111253 | -0.109409 | -0.397194 | -0.354951 | -0.126182 | 0.071709 | 0.448839 | 0.064154 | 0.110712 |
| BOATS_Y | 0.301620 | -0.107099 | -0.105711 | 0.545237 | 0.484858 | -0.052243 | 0.170582 | -0.137156 | 0.032473 | 0.212780 | -0.062768 | -0.003365 | -0.133932 | 0.410728 | 0.091531 | 0.161115 | -0.135389 | -0.110619 | -0.037867 | -0.008389 | -0.006893 | -0.121909 | 0.027894 | -0.073832 | 0.098680 | -0.465161 | -0.079639 | 0.336208 | 0.098350 | 0.131510 | 0.061335 | -0.111253 | 0.109409 | 0.397194 | 0.354951 | 0.126182 | -0.071709 | -0.448839 | -0.064154 | -0.110712 |
| CARDS_ | -0.134180 | -0.582515 | -0.114873 | -0.026854 | -0.006518 | -0.130329 | -0.114972 | 0.254206 | 0.161375 | -0.016396 | 0.011432 | -0.342188 | -0.578453 | -0.173297 | 0.151194 | 0.017338 | 0.045211 | -0.018827 | 0.005831 | 0.010949 | 0.000389 | -0.174374 | -0.094002 | -0.050402 | -0.144208 | 0.235328 | 0.153865 | 0.113042 | 0.156086 | -0.104620 | 0.417075 | -0.264865 | -0.024132 | -0.118951 | -0.164450 | 0.095896 | -0.024673 | 0.053813 | 0.040404 | -0.087373 |
| CARDS_Y | 0.134180 | 0.582515 | 0.114873 | 0.026854 | 0.006518 | 0.130329 | 0.114972 | -0.254206 | -0.161375 | 0.016396 | -0.011432 | 0.342188 | 0.578453 | 0.173297 | -0.151194 | -0.017338 | -0.045211 | 0.018827 | -0.005831 | -0.010949 | -0.000389 | 0.174374 | 0.094002 | 0.050402 | 0.144208 | -0.235328 | -0.153865 | -0.113042 | -0.156086 | 0.104620 | -0.417075 | 0.264865 | 0.024132 | 0.118951 | 0.164450 | -0.095896 | 0.024673 | -0.053813 | -0.040404 | 0.087373 |
| CATLG_ | -0.546227 | 0.041794 | -0.288279 | 0.080797 | 0.003639 | -0.201810 | -0.057507 | -0.127370 | 0.088756 | 0.155897 | 0.678910 | -0.015925 | 0.053292 | -0.029705 | -0.080917 | -0.155772 | -0.025643 | -0.139224 | 0.020749 | 0.005066 | -0.039996 | -0.490600 | 0.100101 | 0.019978 | 0.164576 | -0.069987 | 0.199539 | 0.072380 | -0.052545 | -0.197977 | 0.418418 | -0.291121 | -0.572506 | -0.530603 | -0.440137 | 0.348296 | 0.499127 | -0.081437 | 0.092604 | -0.255866 |
| CATLG_Y | 0.546227 | -0.041794 | 0.288279 | -0.080797 | -0.003639 | 0.201810 | 0.057507 | 0.127370 | -0.088756 | -0.155897 | -0.678910 | 0.015925 | -0.053292 | 0.029705 | 0.080917 | 0.155772 | 0.025643 | 0.139224 | -0.020749 | -0.005066 | 0.039996 | 0.490600 | -0.100101 | -0.019978 | -0.164576 | 0.069987 | -0.199539 | -0.072380 | 0.052545 | 0.197977 | -0.418418 | 0.291121 | 0.572506 | 0.530603 | 0.440137 | -0.348296 | -0.499127 | 0.081437 | -0.092604 | 0.255866 |
| CDPLAY_ | -0.693247 | 0.159884 | -0.333105 | 0.117192 | -0.134481 | 0.155355 | 0.090681 | 0.093087 | 0.120350 | -0.063913 | -0.037341 | 0.003811 | 0.005856 | -0.019897 | 0.025913 | 0.194713 | -0.041004 | 0.108953 | 0.059593 | -0.483603 | -0.008736 | -0.226194 | -0.447046 | 0.198263 | 0.154603 | 0.586751 | 0.377481 | -0.028231 | -0.243845 | -0.420069 | 0.230650 | -0.420591 | -0.412735 | -0.501766 | -0.711677 | 0.410665 | 0.584341 | 0.318363 | 0.309034 | 0.137527 |
| CDPLAY_Y | 0.693247 | -0.159884 | 0.333105 | -0.117192 | 0.134481 | -0.155355 | -0.090681 | -0.093087 | -0.120350 | 0.063913 | 0.037341 | -0.003811 | -0.005856 | 0.019897 | -0.025913 | -0.194713 | 0.041004 | -0.108953 | -0.059593 | 0.483603 | 0.008736 | 0.226194 | 0.447046 | -0.198263 | -0.154603 | -0.586751 | -0.377481 | 0.028231 | 0.243845 | 0.420069 | -0.230650 | 0.420591 | 0.412735 | 0.501766 | 0.711677 | -0.410665 | -0.584341 | -0.318363 | -0.309034 | -0.137527 |
| COLLECT1_ | -0.417857 | -0.465338 | -0.075548 | -0.228979 | 0.266928 | 0.360278 | -0.031852 | -0.222644 | -0.021316 | 0.040756 | -0.009238 | 0.095498 | 0.113523 | -0.036118 | 0.058183 | 0.132100 | 0.415988 | -0.279864 | 0.014769 | -0.033803 | 0.001787 | -0.399149 | -0.348095 | 0.316518 | 0.359797 | 0.049177 | 0.063763 | 0.147548 | -0.046608 | -0.115435 | 0.103129 | -0.082652 | -0.168856 | -0.382730 | -0.418838 | 0.211843 | 0.178704 | -0.044432 | 0.337400 | 0.561979 |
| COLLECT1_Y | 0.417857 | 0.465338 | 0.075548 | 0.228979 | -0.266928 | -0.360278 | 0.031852 | 0.222644 | 0.021316 | -0.040756 | 0.009238 | -0.095498 | -0.113523 | 0.036118 | -0.058183 | -0.132100 | -0.415988 | 0.279864 | -0.014769 | 0.033803 | -0.001787 | 0.399149 | 0.348095 | -0.316518 | -0.359797 | -0.049177 | -0.063763 | -0.147548 | 0.046608 | 0.115435 | -0.103129 | 0.082652 | 0.168856 | 0.382730 | 0.418838 | -0.211843 | -0.178704 | 0.044432 | -0.337400 | -0.561979 |
| CRAFTS_ | -0.562333 | -0.012350 | 0.159561 | -0.135179 | 0.271170 | -0.136053 | -0.007399 | -0.064540 | -0.048352 | 0.471017 | -0.166830 | 0.214882 | -0.093864 | -0.385944 | -0.174516 | 0.063772 | -0.220159 | 0.013256 | -0.027696 | -0.053230 | -0.029978 | -0.458390 | -0.194059 | 0.270495 | 0.377976 | 0.148233 | 0.272364 | 0.329311 | 0.129948 | -0.336038 | 0.260153 | -0.435481 | -0.238705 | -0.493783 | -0.446846 | 0.458400 | 0.455603 | -0.130576 | 0.241845 | 0.058794 |
| CRAFTS_Y | 0.562333 | 0.012350 | -0.159561 | 0.135179 | -0.271170 | 0.136053 | 0.007399 | 0.064540 | 0.048352 | -0.471017 | 0.166830 | -0.214882 | 0.093864 | 0.385944 | 0.174516 | -0.063772 | 0.220159 | -0.013256 | 0.027696 | 0.053230 | 0.029978 | 0.458390 | 0.194059 | -0.270495 | -0.377976 | -0.148233 | -0.272364 | -0.329311 | -0.129948 | 0.336038 | -0.260153 | 0.435481 | 0.238705 | 0.493783 | 0.446846 | -0.458400 | -0.455603 | 0.130576 | -0.241845 | -0.058794 |
| FISHER_ | -0.506819 | 0.077104 | 0.295710 | -0.452445 | -0.267361 | -0.139911 | -0.108435 | -0.077529 | 0.047371 | 0.031636 | 0.047615 | 0.028295 | -0.098776 | 0.360231 | 0.146703 | 0.273344 | -0.204344 | -0.221210 | -0.029066 | -0.021319 | -0.046359 | -0.221927 | -0.327215 | 0.293894 | 0.429598 | -0.139746 | 0.191217 | 0.271993 | -0.448827 | -0.139182 | 0.176386 | -0.174410 | -0.248602 | -0.432987 | -0.493385 | 0.408969 | 0.386648 | -0.075236 | 0.390184 | 0.052415 |
| FISHER_Y | 0.506819 | -0.077104 | -0.295710 | 0.452445 | 0.267361 | 0.139911 | 0.108435 | 0.077529 | -0.047371 | -0.031636 | -0.047615 | -0.028295 | 0.098776 | -0.360231 | -0.146703 | -0.273344 | 0.204344 | 0.221210 | 0.029066 | 0.021319 | 0.046359 | 0.221927 | 0.327215 | -0.293894 | -0.429598 | 0.139746 | -0.191217 | -0.271993 | 0.448827 | 0.139182 | -0.176386 | 0.174410 | 0.248602 | 0.432987 | 0.493385 | -0.408969 | -0.386648 | 0.075236 | -0.390184 | -0.052415 |
| GARDENIN_ | -0.692279 | 0.066559 | 0.221617 | -0.046806 | 0.143809 | -0.100139 | 0.009214 | -0.086020 | 0.052329 | 0.119242 | -0.096817 | -0.127831 | 0.017249 | 0.171568 | 0.133572 | -0.244048 | 0.136071 | 0.200209 | 0.459835 | -0.013761 | -0.082337 | -0.378069 | -0.539459 | 0.021507 | 0.623919 | 0.304834 | 0.618024 | 0.188424 | -0.246615 | -0.424887 | 0.123937 | -0.121124 | -0.099778 | -0.547310 | -0.386079 | 0.665858 | 0.636735 | -0.137478 | 0.498048 | 0.404115 |
| GARDENIN_Y | 0.692279 | -0.066559 | -0.221617 | 0.046806 | -0.143809 | 0.100139 | -0.009214 | 0.086020 | -0.052329 | -0.119242 | 0.096817 | 0.127831 | -0.017249 | -0.171568 | -0.133572 | 0.244048 | -0.136071 | -0.200209 | -0.459835 | 0.013761 | 0.082337 | 0.378069 | 0.539459 | -0.021507 | -0.623919 | -0.304834 | -0.618024 | -0.188424 | 0.246615 | 0.424887 | -0.123937 | 0.121124 | 0.099778 | 0.547310 | 0.386079 | -0.665858 | -0.636735 | 0.137478 | -0.498048 | -0.404115 |
| HOMEE_ | -0.201148 | 0.028360 | -0.359886 | 0.087187 | -0.022000 | -0.279239 | -0.574497 | -0.374414 | -0.445994 | -0.091732 | -0.173518 | -0.122657 | 0.010178 | 0.001453 | 0.009061 | 0.107747 | 0.022901 | 0.089673 | -0.007453 | 0.000589 | 0.005217 | -0.079631 | -0.076387 | -0.059581 | 0.175198 | 0.146914 | 0.188483 | 0.118758 | 0.133794 | -0.258564 | 0.444323 | -0.376853 | -0.541591 | -0.329056 | -0.180022 | 0.178962 | 0.057796 | 0.197048 | -0.042607 | -0.037531 |
| HOMEE_Y | 0.201148 | -0.028360 | 0.359886 | -0.087187 | 0.022000 | 0.279239 | 0.574497 | 0.374414 | 0.445994 | 0.091732 | 0.173518 | 0.122657 | -0.010178 | -0.001453 | -0.009061 | -0.107747 | -0.022901 | -0.089673 | 0.007453 | -0.000589 | -0.005217 | 0.079631 | 0.076387 | 0.059581 | -0.175198 | -0.146914 | -0.188483 | -0.118758 | -0.133794 | 0.258564 | -0.444323 | 0.376853 | 0.541591 | 0.329056 | 0.180022 | -0.178962 | -0.057796 | -0.197048 | 0.042607 | 0.037531 |
| KIDSTUFF_ | -0.127695 | -0.569935 | -0.100122 | 0.034726 | -0.173757 | -0.225120 | -0.112586 | 0.382864 | 0.095971 | 0.229372 | -0.150329 | -0.125478 | 0.385842 | 0.212511 | -0.330531 | 0.052266 | 0.032882 | -0.011128 | 0.009718 | 0.004912 | -0.000567 | -0.111557 | -0.151118 | -0.151553 | -0.209361 | 0.104368 | 0.066885 | 0.133451 | 0.434665 | -0.266654 | -0.183299 | -0.180082 | -0.171949 | -0.303223 | -0.254929 | -0.000860 | 0.095608 | -0.262251 | 0.014017 | 0.160543 |
| KIDSTUFF_Y | 0.127695 | 0.569935 | 0.100122 | -0.034726 | 0.173757 | 0.225120 | 0.112586 | -0.382864 | -0.095971 | -0.229372 | 0.150329 | 0.125478 | -0.385842 | -0.212511 | 0.330531 | -0.052266 | -0.032882 | 0.011128 | -0.009718 | -0.004912 | 0.000567 | 0.111557 | 0.151118 | 0.151553 | 0.209361 | -0.104368 | -0.066885 | -0.133451 | -0.434665 | 0.266654 | 0.183299 | 0.180082 | 0.171949 | 0.303223 | 0.254929 | 0.000860 | -0.095608 | 0.262251 | -0.014017 | -0.160543 |
| LIFESRC_ | -0.711549 | -0.163060 | 0.190428 | 0.308586 | -0.256110 | 0.154240 | -0.114397 | -0.024084 | -0.012386 | 0.149364 | 0.015308 | 0.080934 | 0.053057 | -0.019823 | 0.221151 | -0.070089 | -0.065587 | 0.018475 | -0.020782 | 0.059490 | 0.371056 | -0.383946 | -0.617196 | 0.094296 | 0.339392 | 0.274902 | 0.445243 | 0.173491 | -0.176781 | -0.293195 | 0.001521 | -0.061196 | -0.305238 | -0.611775 | -0.657530 | 0.513893 | 0.489253 | -0.120985 | 0.474322 | 0.114449 |
| LIFESRC_1 | -0.141999 | 0.444030 | -0.210921 | -0.377246 | 0.425280 | -0.237547 | 0.145030 | 0.005827 | 0.185658 | -0.237221 | -0.077874 | -0.173557 | -0.110806 | 0.098628 | -0.379528 | 0.072371 | 0.110573 | -0.032642 | 0.002414 | 0.032048 | 0.158033 | 0.141330 | 0.091262 | -0.022419 | 0.336744 | -0.088499 | -0.040145 | -0.028538 | -0.107725 | 0.009089 | 0.191974 | -0.450938 | -0.143663 | -0.224090 | 0.072115 | 0.015799 | 0.373636 | 0.118024 | 0.045920 | 0.132480 |
| LIFESRC_2 | 0.548542 | -0.354081 | -0.201674 | -0.182226 | 0.009759 | -0.353758 | 0.355039 | -0.017276 | -0.181902 | -0.125482 | -0.010823 | 0.159481 | 0.120361 | -0.080549 | 0.220667 | -0.010688 | -0.030438 | 0.021729 | 0.004501 | -0.075007 | -0.311521 | 0.330448 | 0.395526 | 0.000447 | -0.259396 | -0.079388 | -0.403653 | -0.337004 | 0.354728 | -0.032711 | -0.098844 | 0.330579 | 0.243463 | 0.527360 | 0.259106 | -0.214260 | -0.546236 | -0.058063 | -0.362622 | 0.072055 |
| LIFESRC_3 | 0.528463 | 0.275602 | 0.160586 | 0.112306 | -0.021088 | 0.431138 | -0.406665 | 0.052828 | 0.072759 | 0.152254 | 0.063247 | -0.160306 | -0.127683 | 0.038650 | -0.257287 | 0.052214 | 0.034307 | -0.024743 | 0.023720 | -0.026575 | -0.322376 | 0.037736 | 0.358017 | -0.123024 | -0.506977 | -0.235874 | -0.134108 | 0.184991 | -0.074495 | 0.478568 | -0.058380 | 0.101527 | 0.294032 | 0.480122 | 0.608243 | -0.528270 | -0.410197 | 0.146223 | -0.310411 | -0.388561 |
| PCOWNERS_ | -0.609919 | 0.146005 | -0.386749 | 0.130898 | -0.164737 | 0.106141 | 0.025072 | 0.086638 | 0.065922 | -0.120966 | -0.298059 | 0.163179 | -0.071086 | -0.026873 | -0.032895 | -0.179727 | -0.152772 | -0.356666 | 0.155672 | 0.193418 | -0.087380 | 0.059878 | -0.647850 | -0.249358 | 0.297275 | 0.096649 | 0.174502 | -0.227732 | -0.348795 | -0.275770 | -0.234951 | -0.309391 | -0.435280 | -0.543315 | -0.518190 | 0.343196 | 0.387033 | -0.161555 | 0.331160 | 0.234291 |
| PCOWNERS_Y | 0.609919 | -0.146005 | 0.386749 | -0.130898 | 0.164737 | -0.106141 | -0.025072 | -0.086638 | -0.065922 | 0.120966 | 0.298059 | -0.163179 | 0.071086 | 0.026873 | 0.032895 | 0.179727 | 0.152772 | 0.356666 | -0.155672 | -0.193418 | 0.087380 | -0.059878 | 0.647850 | 0.249358 | -0.297275 | -0.096649 | -0.174502 | 0.227732 | 0.348795 | 0.275770 | 0.234951 | 0.309391 | 0.435280 | 0.543315 | 0.518190 | -0.343196 | -0.387033 | 0.161555 | -0.331160 | -0.234291 |
| PETS_ | -0.711740 | 0.103458 | -0.096234 | -0.016797 | -0.078041 | -0.028957 | 0.023163 | -0.099447 | 0.208843 | 0.111681 | -0.146322 | 0.058008 | -0.063680 | 0.153348 | 0.063220 | -0.209190 | 0.194678 | 0.196507 | -0.454885 | 0.054589 | -0.114969 | -0.455567 | -0.540861 | 0.126032 | 0.466876 | 0.251376 | 0.539541 | 0.224686 | -0.293187 | -0.239904 | 0.061403 | -0.253716 | -0.498910 | -0.496895 | -0.694096 | 0.708150 | 0.695563 | 0.152065 | 0.267908 | 0.168342 |
| PETS_Y | 0.711740 | -0.103458 | 0.096234 | 0.016797 | 0.078041 | 0.028957 | -0.023163 | 0.099447 | -0.208843 | -0.111681 | 0.146322 | -0.058008 | 0.063680 | -0.153348 | -0.063220 | 0.209190 | -0.194678 | -0.196507 | 0.454885 | -0.054589 | 0.114969 | 0.455567 | 0.540861 | -0.126032 | -0.466876 | -0.251376 | -0.539541 | -0.224686 | 0.293187 | 0.239904 | -0.061403 | 0.253716 | 0.498910 | 0.496895 | 0.694096 | -0.708150 | -0.695563 | -0.152065 | -0.267908 | -0.168342 |
| PHOTO_ | -0.471120 | 0.037926 | -0.020605 | -0.142920 | 0.135600 | 0.198613 | 0.129092 | 0.373089 | -0.648908 | 0.058374 | 0.092286 | -0.063551 | -0.122833 | 0.190537 | -0.052548 | -0.190325 | -0.029186 | -0.021290 | -0.098267 | -0.059612 | 0.011215 | -0.009357 | -0.250366 | 0.035667 | 0.403611 | 0.199785 | 0.410491 | 0.348025 | -0.080660 | -0.532316 | 0.004512 | -0.267628 | 0.115675 | -0.186484 | -0.255000 | 0.204789 | 0.428503 | -0.312168 | 0.459420 | 0.067411 |
| PHOTO_Y | 0.471120 | -0.037926 | 0.020605 | 0.142920 | -0.135600 | -0.198613 | -0.129092 | -0.373089 | 0.648908 | -0.058374 | -0.092286 | 0.063551 | 0.122833 | -0.190537 | 0.052548 | 0.190325 | 0.029186 | 0.021290 | 0.098267 | 0.059612 | -0.011215 | 0.009357 | 0.250366 | -0.035667 | -0.403611 | -0.199785 | -0.410491 | -0.348025 | 0.080660 | 0.532316 | -0.004512 | 0.267628 | -0.115675 | 0.186484 | 0.255000 | -0.204789 | -0.428503 | 0.312168 | -0.459420 | -0.067411 |
| PLATES_ | -0.130129 | -0.548367 | -0.129739 | -0.245599 | 0.188496 | 0.351425 | -0.078546 | -0.248693 | 0.128855 | -0.228542 | 0.047455 | -0.005537 | 0.045876 | 0.114468 | -0.117518 | -0.155315 | -0.441017 | 0.242212 | -0.009393 | 0.025503 | 0.001070 | -0.173827 | -0.280633 | 0.081457 | 0.216061 | 0.154554 | -0.373323 | -0.032147 | 0.110957 | 0.095157 | 0.182828 | 0.246374 | 0.099417 | -0.322910 | -0.095523 | 0.004812 | 0.337305 | -0.086430 | 0.107265 | -0.135876 |
| PLATES_Y | 0.130129 | 0.548367 | 0.129739 | 0.245599 | -0.188496 | -0.351425 | 0.078546 | 0.248693 | -0.128855 | 0.228542 | -0.047455 | 0.005537 | -0.045876 | -0.114468 | 0.117518 | 0.155315 | 0.441017 | -0.242212 | 0.009393 | -0.025503 | -0.001070 | 0.173827 | 0.280633 | -0.081457 | -0.216061 | -0.154554 | 0.373323 | 0.032147 | -0.110957 | -0.095157 | -0.182828 | -0.246374 | -0.099417 | 0.322910 | 0.095523 | -0.004812 | -0.337305 | 0.086430 | -0.107265 | 0.135876 |
| STEREO_ | -0.707845 | 0.093999 | -0.124926 | 0.053529 | 0.095868 | 0.116222 | 0.073234 | 0.212000 | -0.033367 | -0.045520 | 0.132207 | 0.015178 | 0.082110 | -0.063505 | 0.092224 | 0.414788 | 0.001071 | 0.259166 | 0.047220 | 0.333017 | -0.078236 | -0.298472 | -0.338646 | 0.081492 | 0.398832 | 0.273184 | 0.505734 | 0.079776 | 0.172307 | -0.516223 | 0.198133 | -0.411102 | -0.343194 | -0.567316 | -0.671642 | 0.367098 | 0.578187 | -0.075517 | 0.394814 | 0.140006 |
| STEREO_Y | 0.707845 | -0.093999 | 0.124926 | -0.053529 | -0.095868 | -0.116222 | -0.073234 | -0.212000 | 0.033367 | 0.045520 | -0.132207 | -0.015178 | -0.082110 | 0.063505 | -0.092224 | -0.414788 | -0.001071 | -0.259166 | -0.047220 | -0.333017 | 0.078236 | 0.298472 | 0.338646 | -0.081492 | -0.398832 | -0.273184 | -0.505734 | -0.079776 | -0.172307 | 0.516223 | -0.198133 | 0.411102 | 0.343194 | 0.567316 | 0.671642 | -0.367098 | -0.578187 | 0.075517 | -0.394814 | -0.140006 |
| VETERANS_ | -0.468440 | -0.218479 | 0.235295 | 0.231925 | -0.338669 | -0.000834 | 0.399898 | -0.360840 | -0.167431 | -0.107745 | 0.001343 | -0.148617 | -0.148226 | -0.021962 | -0.343713 | 0.095524 | 0.059708 | 0.007371 | 0.018188 | 0.036247 | -0.046311 | -0.024691 | -0.343108 | 0.408025 | 0.122549 | 0.173266 | 0.085266 | 0.295077 | 0.172445 | -0.394863 | 0.098280 | -0.143250 | 0.146469 | -0.395847 | -0.373893 | 0.426907 | 0.224690 | 0.183155 | 0.488376 | 0.337305 |
| VETERANS_Y | 0.468440 | 0.218479 | -0.235295 | -0.231925 | 0.338669 | 0.000834 | -0.399898 | 0.360840 | 0.167431 | 0.107745 | -0.001343 | 0.148617 | 0.148226 | 0.021962 | 0.343713 | -0.095524 | -0.059708 | -0.007371 | -0.018188 | -0.036247 | 0.046311 | 0.024691 | 0.343108 | -0.408025 | -0.122549 | -0.173266 | -0.085266 | -0.295077 | -0.172445 | 0.394863 | -0.098280 | 0.143250 | -0.146469 | 0.395847 | 0.373893 | -0.426907 | -0.224690 | -0.183155 | -0.488376 | -0.337305 |
| WALKER_ | -0.586891 | 0.082143 | 0.288181 | 0.145695 | 0.241525 | -0.036892 | -0.000433 | 0.025152 | 0.026188 | -0.203298 | -0.059261 | -0.444768 | 0.301619 | -0.189221 | 0.138105 | -0.040876 | -0.141054 | -0.193219 | -0.169372 | -0.042049 | -0.075193 | -0.044039 | -0.209584 | 0.323438 | 0.395150 | -0.002884 | 0.377417 | 0.334940 | -0.034458 | -0.270705 | 0.136011 | -0.356489 | -0.236533 | -0.437326 | -0.467331 | 0.521255 | 0.358560 | -0.171060 | 0.614969 | 0.111092 |
| WALKER_Y | 0.586891 | -0.082143 | -0.288181 | -0.145695 | -0.241525 | 0.036892 | 0.000433 | -0.025152 | -0.026188 | 0.203298 | 0.059261 | 0.444768 | -0.301619 | 0.189221 | -0.138105 | 0.040876 | 0.141054 | 0.193219 | 0.169372 | 0.042049 | 0.075193 | 0.044039 | 0.209584 | -0.323438 | -0.395150 | 0.002884 | -0.377417 | -0.334940 | 0.034458 | 0.270705 | -0.136011 | 0.356489 | 0.236533 | 0.437326 | 0.467331 | -0.521255 | -0.358560 | 0.171060 | -0.614969 | -0.111092 |
dic['df_corr5'] #OVERLAY DATA
| PC0 | PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | PC9 | PC10 | PC11 | PC12 | PC13 | PC14 | PC15 | PC16 | PC17 | PC18 | PC19 | PC20 | PC21 | PC22 | PC23 | PC24 | PC25 | PC26 | PC27 | PC28 | PC29 | PC30 | PC31 | PC32 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| DATASRCE_ | -0.012396 | -0.045419 | 0.057961 | 0.035035 | -0.010321 | 0.014393 | -0.039554 | 0.016339 | 0.034602 | -0.034969 | 0.053294 | -0.041453 | 0.018790 | -0.009758 | 0.017704 | -0.051733 | 0.015774 | 0.037858 | 0.033436 | 0.033961 | 0.033755 | -0.031861 | -0.050508 | -0.009332 | -0.010417 | 0.033989 | 0.009269 | -0.000631 | 0.062171 | 0.036665 | 0.026734 | -0.016327 | -0.024252 |
| DATASRCE_1 | 0.001693 | 0.006753 | -0.039657 | 0.005262 | -0.013565 | 0.000221 | 0.014189 | -0.021029 | -0.016309 | 0.017204 | -0.026283 | 0.028595 | 0.012405 | 0.017409 | 0.002859 | 0.004935 | 0.012924 | -0.022119 | -0.001572 | -0.005273 | -0.016094 | 0.018615 | 0.023199 | -0.017642 | 0.000202 | -0.034938 | -0.003793 | 0.006135 | -0.021911 | -0.019683 | -0.017485 | 0.020825 | 0.023005 |
| DATASRCE_2 | 0.002808 | -0.008165 | 0.067690 | -0.018190 | 0.026847 | -0.002137 | -0.013090 | 0.021121 | 0.009126 | -0.003509 | 0.045566 | -0.052956 | -0.025434 | -0.027404 | -0.010175 | 0.000930 | -0.016780 | 0.016689 | 0.005982 | -0.003534 | 0.012802 | -0.016150 | -0.025217 | 0.043746 | 0.002531 | 0.066035 | 0.022719 | -0.007871 | 0.037765 | 0.028324 | 0.016901 | -0.015983 | -0.039647 |
| DATASRCE_3 | 0.006933 | 0.041123 | -0.085834 | -0.015985 | -0.007613 | -0.010176 | 0.036628 | -0.020782 | -0.027975 | 0.022933 | -0.069814 | 0.065209 | -0.000013 | 0.022692 | -0.007330 | 0.039415 | -0.005299 | -0.034175 | -0.032037 | -0.022268 | -0.030576 | 0.030586 | 0.051475 | -0.020948 | 0.006320 | -0.067040 | -0.025389 | 0.004123 | -0.072694 | -0.044564 | -0.027589 | 0.016422 | 0.042366 |
| FEDGOV | 0.685632 | 0.470959 | 0.176328 | 0.371183 | 0.028457 | 0.017450 | 0.040144 | -0.102722 | -0.007572 | -0.022171 | -0.443109 | 0.476174 | 0.402057 | 0.772716 | 0.164354 | -0.376358 | 0.414136 | -0.397822 | 0.121132 | 0.253619 | 0.050540 | -0.054750 | 0.013702 | 0.412105 | 0.084304 | 0.001861 | 0.462563 | 0.089508 | -0.154198 | 0.500529 | 0.160734 | -0.314090 | 0.366344 |
| GEOCODE_ | -0.071176 | 0.015796 | 0.354341 | -0.028084 | 0.079161 | -0.025402 | -0.120053 | 0.090934 | 0.002964 | 0.021438 | 0.216589 | -0.262613 | -0.152761 | -0.171035 | -0.054168 | 0.015326 | -0.103705 | 0.084112 | 0.042672 | -0.031412 | 0.023862 | -0.045534 | -0.092603 | 0.155113 | -0.115159 | 0.356114 | 0.087652 | -0.023923 | 0.149611 | 0.110540 | 0.056647 | -0.097730 | -0.282782 |
| GEOCODE_01 | -0.061223 | -0.002883 | -0.149640 | 0.045283 | -0.058017 | 0.027244 | 0.028782 | -0.060229 | 0.005012 | -0.019817 | -0.070624 | 0.096152 | 0.057277 | 0.043879 | -0.005125 | -0.005219 | 0.032606 | -0.016593 | 0.007162 | 0.016399 | -0.006352 | 0.014474 | 0.040502 | -0.138960 | -0.037749 | -0.159884 | -0.040628 | 0.016961 | -0.063969 | -0.067042 | -0.033026 | 0.067214 | 0.053384 |
| GEOCODE_02 | 0.005818 | -0.034933 | -0.152052 | 0.000396 | -0.036441 | 0.017059 | 0.033062 | -0.052143 | -0.016937 | 0.004827 | -0.084557 | 0.102777 | 0.039987 | 0.051051 | 0.032637 | 0.014050 | 0.042995 | -0.046179 | -0.021432 | 0.014862 | -0.025424 | 0.034767 | 0.049649 | -0.073485 | 0.043702 | -0.145791 | -0.031305 | 0.002310 | -0.044587 | -0.078619 | -0.046192 | 0.068176 | 0.106299 |
| GEOCODE_03 | 0.137827 | -0.085444 | -0.199312 | -0.064789 | -0.021499 | -0.018703 | 0.079606 | -0.027324 | -0.029977 | 0.029580 | -0.131858 | 0.146050 | 0.066684 | 0.076273 | 0.026190 | 0.004381 | 0.057706 | -0.035664 | -0.057024 | -0.021512 | -0.040515 | 0.057015 | 0.060573 | 0.030871 | 0.206554 | -0.170210 | -0.023514 | 0.032819 | -0.051231 | -0.064441 | -0.019723 | 0.061579 | 0.243675 |
| GEOCODE_04 | 0.018767 | -0.013031 | -0.137356 | -0.020411 | -0.023721 | -0.020254 | 0.083382 | 0.007038 | 0.024878 | -0.026129 | -0.064133 | 0.072071 | 0.063539 | 0.063527 | 0.047693 | 0.015095 | 0.017283 | -0.020971 | -0.031395 | -0.019673 | 0.006719 | -0.001132 | 0.014786 | -0.048060 | 0.062935 | -0.140645 | -0.004591 | -0.016146 | -0.067482 | -0.030919 | 0.002018 | 0.040359 | 0.111755 |
| GEOCODE_05 | -0.059611 | 0.052132 | -0.173381 | 0.010914 | -0.004016 | 0.046224 | 0.066550 | -0.020603 | 0.033196 | -0.059059 | -0.067077 | 0.095576 | 0.079911 | 0.075238 | 0.001627 | -0.008583 | 0.027227 | -0.026983 | -0.010585 | 0.025981 | 0.027916 | -0.021800 | 0.027543 | -0.160669 | -0.036945 | -0.192322 | -0.033879 | 0.025658 | -0.107250 | -0.036861 | -0.017606 | 0.067619 | 0.051572 |
| GEOCODE_12 | 0.154732 | -0.020213 | -0.012224 | 0.034992 | -0.001560 | 0.014656 | -0.011807 | -0.018838 | 0.003065 | -0.001259 | -0.056146 | 0.069035 | 0.062268 | 0.089268 | 0.033906 | -0.034137 | 0.069496 | -0.042360 | 0.011030 | 0.039308 | 0.007066 | 0.002905 | -0.005157 | 0.068501 | 0.112387 | -0.022122 | -0.043198 | -0.020215 | 0.030211 | 0.034306 | 0.000020 | -0.053300 | 0.130711 |
| GEOCODE_14 | -0.135609 | 0.093564 | -0.104308 | 0.084728 | -0.077734 | 0.007505 | 0.032087 | -0.072744 | -0.018892 | 0.001373 | -0.061548 | 0.074330 | 0.006362 | 0.008157 | -0.011796 | -0.011040 | -0.008807 | -0.014013 | 0.000829 | 0.021919 | -0.027620 | 0.022825 | 0.056654 | -0.174291 | -0.165299 | -0.108824 | -0.042010 | 0.023254 | -0.112328 | -0.071290 | -0.042918 | 0.036899 | -0.055885 |
| LOCALGOV | -0.000829 | 0.530407 | -0.007983 | -0.451870 | 0.330898 | -0.416311 | 0.809768 | 0.870576 | 0.546595 | -0.472080 | 0.268175 | -0.397537 | 0.247951 | 0.109312 | 0.309022 | 0.208837 | -0.674547 | 0.366605 | -0.670755 | -0.624062 | 0.524112 | -0.593404 | -0.447751 | 0.088699 | 0.156687 | -0.054375 | 0.003562 | -0.027776 | -0.616695 | 0.517749 | 0.603763 | -0.467503 | -0.045246 |
| MAJOR_ | 0.006434 | 0.037294 | 0.009218 | -0.020251 | 0.014431 | -0.006039 | 0.009874 | 0.005089 | -0.020080 | 0.020180 | -0.010755 | -0.002427 | -0.027410 | 0.000068 | -0.021274 | 0.028076 | -0.019100 | -0.014755 | -0.015545 | -0.017328 | -0.014790 | 0.010704 | 0.019394 | 0.064511 | -0.007722 | 0.023375 | -0.006128 | 0.006601 | -0.023068 | -0.000343 | -0.008849 | -0.010887 | -0.020982 |
| MAJOR_X | -0.006434 | -0.037294 | -0.009218 | 0.020251 | -0.014431 | 0.006039 | -0.009874 | -0.005089 | 0.020080 | -0.020180 | 0.010755 | 0.002427 | 0.027410 | -0.000068 | 0.021274 | -0.028076 | 0.019100 | 0.014755 | 0.015545 | 0.017328 | 0.014790 | -0.010704 | -0.019394 | -0.064511 | 0.007722 | -0.023375 | 0.006128 | -0.006601 | 0.023068 | 0.000343 | 0.008849 | 0.010887 | 0.020982 |
| MALEMILI | 0.661081 | 0.268662 | 0.252881 | 0.571358 | -0.099378 | 0.073215 | -0.105289 | -0.044084 | 0.214896 | -0.218547 | -0.173634 | 0.279888 | 0.512817 | 0.611884 | 0.282495 | -0.459050 | 0.312883 | -0.093220 | 0.100910 | 0.342069 | 0.263821 | -0.241565 | -0.256118 | 0.170758 | 0.128602 | 0.075811 | -0.433289 | -0.037967 | 0.066504 | 0.468300 | 0.202718 | -0.695671 | 0.346955 |
| MALEVET | -0.039352 | 0.776393 | -0.333301 | -0.075790 | -0.016034 | -0.165548 | 0.334382 | -0.254248 | -0.495977 | 0.480406 | -0.649280 | 0.457403 | -0.361509 | 0.091941 | -0.216844 | 0.552946 | -0.205765 | -0.507787 | -0.248017 | -0.275091 | -0.486768 | 0.426127 | 0.619794 | 0.099008 | -0.379344 | -0.108372 | -0.084991 | -0.293126 | -0.650447 | -0.364158 | -0.454759 | 0.064431 | -0.117950 |
| SOLIH_00 | 0.033498 | 0.050211 | -0.019678 | -0.035150 | 0.019474 | -0.009623 | 0.031139 | 0.004374 | -0.029632 | 0.028231 | -0.038215 | 0.027422 | -0.020230 | -0.001599 | -0.022879 | 0.047048 | -0.017944 | -0.027510 | -0.029401 | -0.028583 | -0.021713 | 0.019526 | 0.033816 | 0.012916 | 0.018960 | 0.003889 | -0.019688 | 0.024163 | -0.051159 | -0.004329 | -0.010634 | -0.017382 | 0.012305 |
| SOLIH_01 | -0.005107 | -0.006104 | 0.001313 | 0.005574 | -0.000530 | 0.005971 | -0.007271 | -0.005133 | 0.000766 | -0.002706 | 0.002634 | 0.001474 | 0.002464 | -0.026095 | 0.013027 | -0.006546 | 0.007436 | -0.000563 | 0.017239 | 0.001806 | 0.001438 | -0.001543 | -0.000467 | 0.015484 | -0.004761 | -0.001704 | 0.002772 | -0.000435 | 0.006582 | -0.001660 | -0.001537 | 0.004944 | -0.001666 |
| SOLIH_02 | -0.002457 | 0.004206 | -0.001733 | 0.005250 | -0.001111 | 0.001179 | 0.001866 | -0.000237 | 0.003705 | -0.005111 | -0.000659 | 0.001852 | 0.004158 | 0.003190 | -0.000032 | -0.000562 | 0.014379 | 0.022667 | -0.013919 | -0.004742 | 0.003584 | -0.003791 | -0.002185 | -0.003361 | -0.005288 | -0.004720 | 0.002534 | 0.005270 | -0.001649 | 0.003057 | 0.002902 | -0.001742 | -0.000551 |
| SOLIH_03 | -0.007225 | -0.007989 | 0.003164 | 0.004499 | -0.004118 | -0.000508 | -0.002186 | 0.003702 | 0.008963 | 0.005113 | -0.001039 | -0.009606 | 0.004418 | -0.004109 | 0.009263 | -0.012304 | -0.000240 | 0.008003 | -0.001022 | 0.005341 | 0.007779 | -0.005997 | 0.006658 | -0.009765 | -0.002703 | -0.000920 | 0.001054 | -0.003530 | 0.007019 | 0.003234 | 0.006642 | -0.000474 | -0.003392 |
| SOLIH_04 | 0.003516 | -0.004420 | 0.005029 | 0.002148 | -0.002576 | -0.003196 | -0.001692 | 0.001111 | 0.001011 | 0.001508 | 0.004206 | -0.004332 | 0.004801 | -0.010831 | -0.001135 | 0.014532 | -0.004890 | 0.016148 | -0.007218 | 0.018814 | 0.000108 | -0.000908 | -0.003569 | 0.011970 | 0.003647 | 0.005762 | -0.006520 | 0.000295 | 0.004306 | 0.000419 | 0.002390 | -0.008366 | 0.001637 |
| SOLIH_06 | -0.002376 | -0.000463 | 0.001881 | -0.001229 | -0.001564 | -0.006017 | 0.005113 | 0.007000 | 0.005244 | 0.004341 | 0.016091 | -0.001523 | 0.000018 | -0.004803 | 0.003137 | -0.000513 | -0.006291 | 0.003383 | -0.009873 | -0.003085 | 0.006894 | 0.000752 | -0.007663 | 0.006629 | 0.000455 | 0.001723 | -0.000852 | 0.002721 | -0.001020 | 0.005389 | 0.008255 | -0.003722 | -0.001015 |
| SOLIH_12 | -0.032809 | -0.050037 | 0.019511 | 0.034068 | -0.019168 | 0.009296 | -0.030903 | -0.004279 | 0.028841 | -0.028285 | 0.037815 | -0.027455 | 0.019241 | 0.005685 | 0.020990 | -0.047024 | 0.016106 | 0.023903 | 0.030103 | 0.028143 | 0.020770 | -0.018848 | -0.033956 | -0.015136 | -0.018105 | -0.003513 | 0.019698 | -0.025051 | 0.050754 | 0.003855 | 0.009860 | 0.017866 | -0.012093 |
| SOLP3_00 | 0.000547 | 0.004589 | 0.002765 | -0.000303 | -0.003669 | -0.007983 | 0.005190 | 0.002163 | -0.001844 | -0.013967 | -0.007552 | -0.004547 | -0.000786 | -0.009038 | -0.001111 | -0.001840 | -0.006611 | -0.002207 | -0.012716 | -0.005459 | 0.000237 | 0.004557 | 0.003643 | 0.005322 | -0.001051 | 0.005231 | -0.000498 | 0.007273 | -0.007717 | 0.003589 | 0.003325 | -0.005786 | -0.002836 |
| SOLP3_01 | -0.001767 | 0.004046 | -0.006786 | -0.003582 | 0.004709 | 0.006767 | -0.002771 | -0.006766 | -0.007412 | 0.020412 | -0.017884 | 0.005331 | -0.007617 | -0.001101 | -0.009296 | 0.010467 | 0.004207 | -0.012414 | 0.005915 | 0.002860 | -0.007000 | 0.006101 | -0.005543 | -0.000943 | -0.003116 | -0.004387 | -0.002181 | -0.008379 | -0.000757 | -0.006993 | -0.011789 | 0.009064 | -0.000953 |
| SOLP3_02 | -0.000292 | 0.002543 | -0.001970 | -0.001935 | 0.003614 | 0.004624 | -0.002536 | -0.004847 | -0.005810 | 0.006350 | -0.003617 | 0.004061 | -0.006118 | 0.012489 | 0.008366 | 0.010322 | -0.000582 | 0.021331 | 0.018912 | 0.001655 | -0.003207 | 0.004853 | 0.006499 | -0.001459 | -0.001939 | -0.000309 | -0.001169 | -0.003354 | -0.000399 | -0.006813 | -0.006252 | 0.002614 | -0.002745 |
| SOLP3_12 | 0.000366 | -0.008308 | 0.000908 | 0.002842 | 0.000679 | 0.004341 | -0.003818 | 0.002556 | 0.007905 | 0.003752 | 0.019271 | 0.001239 | 0.006872 | 0.007032 | 0.003327 | -0.006653 | 0.005775 | 0.001930 | 0.005603 | 0.004379 | 0.004391 | -0.010094 | -0.003564 | -0.005271 | 0.003481 | -0.003770 | 0.002095 | -0.003098 | 0.009569 | 0.001651 | 0.004247 | 0.001247 | 0.004724 |
| STATEGOV | 0.108166 | 0.270888 | 0.104687 | -0.411467 | 0.939789 | 0.818148 | -0.372804 | 0.043238 | -0.039606 | -0.182847 | 0.107834 | -0.055676 | -0.159088 | 0.192575 | -0.763647 | 0.399398 | 0.396525 | -0.587980 | 0.563056 | 0.489786 | 0.245946 | -0.224465 | 0.089873 | 0.024781 | 0.017399 | 0.044245 | -0.010746 | -0.053336 | 0.253134 | 0.156003 | -0.351843 | 0.326173 | -0.252248 |
| VIETVETS | 0.675868 | 0.013332 | -0.164591 | -0.485032 | 0.188118 | -0.186190 | 0.189344 | -0.012833 | -0.433495 | 0.475326 | -0.410657 | 0.271085 | -0.282263 | -0.050252 | -0.184305 | 0.411817 | -0.066422 | -0.240532 | -0.325242 | -0.314767 | -0.384414 | 0.394079 | 0.381776 | 0.747861 | 0.709711 | 0.162390 | -0.129360 | 0.278178 | -0.182730 | -0.160552 | -0.129700 | -0.080524 | 0.474933 |
| WEALTH2 | 0.154560 | -0.127718 | -0.905854 | -0.015229 | -0.123443 | 0.119302 | 0.280352 | -0.192543 | 0.027309 | -0.100997 | -0.495397 | 0.626274 | 0.404993 | 0.437161 | 0.110233 | -0.034152 | 0.308044 | -0.220500 | -0.058129 | 0.100601 | -0.016399 | 0.078074 | 0.205667 | -0.407077 | 0.352790 | -0.945236 | -0.099529 | 0.060984 | -0.315758 | -0.270551 | -0.133118 | 0.357527 | 0.726875 |
| WWIIVETS | -0.625100 | 0.584149 | -0.105538 | 0.159038 | -0.031176 | 0.080733 | 0.098380 | -0.086616 | -0.035702 | -0.053567 | -0.023462 | 0.026928 | -0.109265 | -0.112262 | -0.243678 | 0.072542 | -0.205134 | 0.014590 | -0.025960 | -0.004949 | 0.002894 | -0.046846 | 0.141381 | -0.575525 | -0.803842 | -0.099582 | -0.112736 | 0.409544 | -0.490669 | -0.062007 | -0.013904 | 0.005006 | -0.568669 |
#dic['df_corr6'] #PROMOTION HISTORY
#update features list
for i in range(len(group)):
names=[]
#iterating from the dictionary to preserve the order of feature importance
for f in dic['most_important_names'+str(i)]:
#remove blank spaces
for var in group.loc[i,'Var'].replace(' ','').split(','):
#append the most relevant features per group
if var in f.strip(' ') and var not in names: names.append(var)
#update group dataframe with the new set of features
group.loc[i,'Feature']=','.join(map(str,names))
#getting phi_k correlation matrix from pandas profiling
def get_phi_k_corr(df,title):
profile=ProfileReport(df.iloc[:,1:], title=title, correlations={'pearson':{'calculate':False},'spearman':{'calculate':False}, 'kendall':{'calculate':False},'phi_k':{'calculate':True},'cramers':{'calculate':False},})
phi_k=pd.DataFrame([])
dict=profile.description_set
for keys,values in dict.items():
try:
for keys_ in dict.get(keys).keys():
try:
if keys_=='phi_k':
phi_k=pd.concat([phi_k,dict.get(keys).get(keys_)])
except AttributeError as e:
pass
except AttributeError as e:
pass
return phi_k
#print correlation matrix
def print_corr_matrix(df,title,k=1):
plt.title(str.upper(title), size=20*k)
mask=np.triu(np.ones_like(df, dtype=np.bool))
sns.set(rc={'figure.figsize':(15*k,8*k)})
sns.heatmap(df,xticklabels=df.columns, yticklabels=df.columns,
annot=True,linewidths=.5,vmin=-1.0,vmax=1.0,
mask=mask,cmap=sns.diverging_palette(-10,240,sep=70,n=7),fmt='.2')
plt.show()
def remove_high_corr(df,factor=0.75):
while True:
corr_df = df.apply(lambda i: i > factor)
corr_df['summary'] = corr_df.eq(True).sum(axis=1)
metric_vars_purge = list(corr_df.loc[corr_df['summary'] > 1].index)
if len(metric_vars_purge) > 0:
df.drop(columns=[metric_vars_purge[0]], inplace=True)
df.drop(labels=[metric_vars_purge[0]], inplace=True)
return df
#call pandas profiling to retrieve phik correlation matrix for each group
for i in range(len(group)):
dic['phi_k'+str(i)]=get_phi_k_corr(cleaned_data.loc[:,group.loc[i,'Feature'].split(',')].reset_index(),'')
print_corr_matrix(dic['phi_k0'],group.loc[0,'Group'])
cluster_feat='RFA_2F,RFA_2A'
print_corr_matrix(dic['phi_k1'],group.loc[1,'Group'],4)
cluster_feat+=',IC3,HHD2,ETHC3'
print_corr_matrix(dic['phi_k2'],group.loc[2,'Group'])
cluster_feat+=',INCOME,AGE,N_ODATEDW,NUMCHLD'
print_corr_matrix(dic['phi_k3'],group.loc[3,'Group'])
cluster_feat+=',PETS'
print_corr_matrix(dic['phi_k4'],group.loc[4,'Group'])
cluster_feat+=',N_RDATE_7,RAMNT_7'
print_corr_matrix(dic['phi_k5'],group.loc[5,'Group'])
cluster_feat+=',FEDGOV,VIETVETS'
print_corr_matrix(dic['phi_k6'],group.loc[6,'Group'],2)
cluster_feat+=',N_ADATE_7'
print_corr_matrix(dic['phi_k7'],group.loc[7,'Group'])
cluster_feat+=',MBBOOKS,MBGARDEN'
print_corr_matrix(dic['phi_k8'],group.loc[8,'Group'])
cluster_feat+=',N_FISTDATE,MAXRAMNT,N_LASTDATE,N_MAXRDATE'
print_corr_matrix(dic['phi_k9'],group.loc[9,'Group'])
cluster_feat+=',CARDPROM'
def plot_cluster_umap(embedding,labels,s,title='Cluster'):
fig, ax = plt.subplots()
fig.set_size_inches((20, 10))
scatter = ax.scatter(embedding[:,0], embedding[:,1], s=s, c=labels, cmap='tab20b', alpha=1.0)
#produce a legend with the unique colors from the scatter
legend = ax.legend(*scatter.legend_elements(num=max(labels)+1), loc='lower left', title=title)
ax.add_artist(legend)
def kelbowplots(model, df):
"""
This function produces the k-elbow plot for a given clustering estimator according to 3 different clustering quality measures: Distortion, Silhouette and Calinski Harabasz.
"""
fig, axes = plt.subplots(1,3,figsize=(40,14))
metrics = ['distortion', 'silhouette', 'calinski_harabasz']
ylabels = ['Distortion Measure', 'Silhouette Measure', 'Calinski Harabasz Measure']
titles = ['Distortion Measure Plot', 'Silhouette Measure Plot', 'Calinski Harabasz Measure Plot']
for ax, mtr, yl, tl in zip(axes.flatten(), metrics, ylabels, titles):
#produce the elbow plot for several quality measures & fit the data to the visualizer
KElbowVisualizer(model, metric=mtr, ax=ax, k=(2,20)).fit(df)
ax.invert_xaxis()
ax.set_ylabel(yl, fontsize=30)
ax.set_xlabel('Number of clusters', fontsize=30)
ax.set_title(tl, fontsize=30)
#render the figure
plt.suptitle('K-Elbow Plots', fontsize=40)
plt.show()
# Create a dataframe with the selected features based on PCA & Phik correlation analysis
cluster_data=cleaned_data.loc[:,cluster_feat.split(',')]
# Get data for clustering
# Standardize input data because we want every one of them to have the same importance
kmeans_data=cluster_data.select_dtypes(include='number').copy()
for i in kmeans_data.columns.tolist():
kmeans_data.loc[:,i]=PowerTransformer(method='yeo-johnson').fit_transform(np.array(kmeans_data[i]).reshape(-1, 1))
# Call function passing kmeans as object for initalization & display elbow plot
kelbowplots(KMeans(random_state=random_state), kmeans_data)
# Using the quick method and immediately show the figure
kelbow_visualizer(KMeans(random_state=random_state), kmeans_data, k=(2,20))
plt.show()
# Using the quick method and immediately show the figure
for i in range(5,11):
silhouette_visualizer(KMeans(i,random_state=random_state), kmeans_data, colors='yellowbrick')
plt.show()
# K-means for metric features
kmeans=KMeans(n_clusters=8, init='k-means++', max_iter=1000, tol=0.0001).fit(kmeans_data)
kmeans_labels=kmeans.labels_
# Count of row observations per cluster
kmeans_summary=pd.DataFrame(pd.Series(kmeans_labels).value_counts().sort_index(axis=0),columns=['Observations'])
kmeans_summary.index.name='Cluster'
kmeans_summary
| Observations | |
|---|---|
| Cluster | |
| 0 | 8053 |
| 1 | 13230 |
| 2 | 15305 |
| 3 | 18086 |
| 4 | 7522 |
| 5 | 8820 |
| 6 | 2161 |
| 7 | 17485 |
# Characterizing the final clusters
df_concat=cluster_data.copy()
df_concat['Cluster'] = kmeans_labels
df_concat.groupby('Cluster').mean().T
| Cluster | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
|---|---|---|---|---|---|---|---|---|
| RFA_2F | 2.363964 | 1.816478 | 2.682457 | 1.757381 | 1.861473 | 1.809864 | 1.900046 | 1.180040 |
| IC3 | 378.654539 | 515.369690 | 343.830774 | 328.276623 | 387.808562 | 417.083333 | 372.906525 | 388.383929 |
| HHD2 | 71.783186 | 81.484958 | 69.322313 | 65.459306 | 71.881415 | 76.539229 | 73.445627 | 71.424650 |
| ETHC3 | 17.048553 | 10.378005 | 20.428814 | 19.389307 | 17.392316 | 13.535147 | 17.728829 | 18.159794 |
| INCOME | 3.780330 | 4.861376 | 3.151454 | 3.513989 | 3.841797 | 4.646712 | 3.676076 | 3.926108 |
| AGE | 59.247734 | 53.346334 | 66.898661 | 57.679752 | 59.506514 | 47.905669 | 61.849607 | 62.130226 |
| N_ODATEDW | 112.115237 | 89.684958 | 150.471480 | 76.244830 | 112.042675 | 103.996939 | 125.219806 | 149.168544 |
| NUMCHLD | 0.192972 | 0.000151 | 0.039660 | 0.010118 | 0.168040 | 1.548413 | 0.257288 | 0.024650 |
| N_RDATE_7 | 58.100211 | 612.000000 | 612.000000 | 612.000000 | 612.000000 | 612.000000 | 557.402129 | 612.000000 |
| RAMNT_7 | 15.528080 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1.465988 | 0.000000 |
| FEDGOV | 3.006830 | 4.183900 | 2.761777 | 2.595156 | 3.067136 | 3.562585 | 3.155484 | 2.886017 |
| VIETVETS | 29.783807 | 39.696977 | 26.580660 | 25.218733 | 29.766419 | 33.833560 | 30.317446 | 28.466686 |
| N_ADATE_7 | 59.409661 | 59.477627 | 65.183665 | 59.128829 | 612.000000 | 61.187868 | 105.622397 | 59.034430 |
| MBBOOKS | 0.430274 | 0.474754 | 0.470631 | 0.333407 | 0.410795 | 0.560998 | 2.495604 | 0.521990 |
| MBGARDEN | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1.106432 | 0.000000 |
| N_FISTDATE | 108.312058 | 88.207181 | 143.515322 | 75.951288 | 108.425020 | 101.198526 | 120.300787 | 142.287961 |
| MAXRAMNT | 18.179142 | 20.903785 | 14.413355 | 20.057312 | 19.419880 | 19.569920 | 18.670292 | 26.387350 |
| N_LASTDATE | 57.803303 | 62.004535 | 59.708853 | 61.738748 | 60.194097 | 62.218594 | 61.226284 | 63.968316 |
| N_MAXRDATE | 72.558053 | 66.641497 | 83.392682 | 64.332799 | 71.536294 | 70.048639 | 75.725590 | 83.121704 |
| CARDPROM | 17.682975 | 13.887150 | 25.794642 | 10.649121 | 15.985243 | 16.449887 | 20.259602 | 25.355676 |
# Performing inertia to validate the previous number of clusters
sse={}
for k in tqdm(range(2, 20)):
kmeans_i=KMeans(n_clusters=k, max_iter=1000).fit(kmeans_data)
sse[k]=kmeans_i.inertia_#inertia: sum of distances of samples to their closest cluster center
# Plot inertia using plotly library
fig=go.Figure(data=go.Scatter(x=list(sse.keys()), y=list(sse.values())))
fig.show()
100%|██████████| 18/18 [01:02<00:00, 3.49s/it]
#embedding_kmeans=apply_umap(kmeans_data)
fit1_ = umap.UMAP(metric='l2').fit(kmeans_data)
embedding_kmeans = umap.umap_.simplicial_set_embedding(fit1_._raw_data,fit1_.graph_,fit1_.n_components,
fit1_._initial_alpha, fit1_._a, fit1_._b,
fit1_.repulsion_strength, fit1_.negative_sample_rate,
200, 'random', np.random, fit1_.metric,
fit1_._metric_kwds, False)
sns.set_style('white')
plot_cluster_umap(embedding_kmeans,kmeans_labels,3,'Cluster')
def plot_clusters(data, algorithm, args, kwds):
labels = algorithm(*args, **kwds).fit_predict(data)
palette = sns.color_palette('deep',np.unique(labels).max()+1)
colors = [palette[i] if i>= 0 else (0.0, 0.0, 0.0) for i in labels]
plt_kwds={'alpha':0.25,'s':2,'linewidths':0}
plt.scatter(data.T[0], data.T[1], c=colors, **plt_kwds)
frame=plt.gca()
frame.axes.get_xaxis().set_visible(False)
frame.axes.get_yaxis().set_visible(False)
plt.title('Clusters found by {}'.format(str(algorithm.__name__)), fontsize=20)
plot_clusters(embedding_kmeans, KMeans, (), {'n_clusters':8})
From the graph above we can conclude that the 8 clusters are clearly distinguishable by using the "deep" color palette
Intercluster distance maps display an embedding of the cluster centers in 2 dimensions with the distance to other centers preserved, the closer to centers are in the visualization, the closer they are in the original feature space. The clusters are sized according to a scoring metric this gives a sense of the relative importance of clusters however, that because two clusters overlap in the 2D space, it does not imply that they overlap in the original feature space
#Instantiate the clustering model and visualizer
view=InterclusterDistance(KMeans(8,random_state=4))
#Fit the data to the visualizer
view.fit(embedding_kmeans)
#Render the figure
view.show()
plt.show()
kproto_data = cluster_data.copy()
for i in kproto_data.select_dtypes(include='number').columns.tolist():
kproto_data[i] = PowerTransformer(method='yeo-johnson').fit_transform(np.array(kproto_data[i]).reshape(-1, 1))
kproto=KPrototypes(n_clusters=8, init='Cao', n_jobs=4)
kproto_categorical=[]
for i,j in enumerate(kproto_data.columns):
if j in list(kproto_data.select_dtypes(include='object').columns):
kproto_categorical.append(i)
kproto_labels=kproto.fit_predict(kproto_data, categorical=kproto_categorical)
#Count of row observations per cluster
kproto_summary=pd.DataFrame(pd.Series(kproto_labels).value_counts().sort_index(axis=0),columns=['Observations'])
kproto_summary.index.name='Cluster'
kproto_summary
| Observations | |
|---|---|
| Cluster | |
| 0 | 8825 |
| 1 | 8053 |
| 2 | 13255 |
| 3 | 2161 |
| 4 | 14917 |
| 5 | 18139 |
| 6 | 17835 |
| 7 | 7477 |
# Characterizing the final clusters
df_concat=cluster_data.copy()
df_concat['Cluster'] = kproto_labels
df_concat.groupby('Cluster').mean().T
| Cluster | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
|---|---|---|---|---|---|---|---|---|
| RFA_2F | 1.805666 | 2.363964 | 1.791173 | 1.900046 | 2.731045 | 1.764155 | 1.188842 | 1.852347 |
| IC3 | 416.953881 | 378.654539 | 517.811166 | 372.906525 | 346.126902 | 328.511329 | 383.329016 | 388.207302 |
| HHD2 | 76.539717 | 71.783186 | 81.539419 | 73.445627 | 69.735671 | 65.558465 | 70.889263 | 71.895011 |
| ETHC3 | 13.540170 | 17.048553 | 10.351943 | 17.728829 | 20.115171 | 19.360880 | 18.537987 | 17.358700 |
| INCOME | 4.646459 | 3.780330 | 4.874312 | 3.676076 | 3.174834 | 3.518055 | 3.872049 | 3.850207 |
| AGE | 47.927139 | 59.247734 | 53.408223 | 61.849607 | 66.700677 | 57.634765 | 62.450687 | 59.413267 |
| N_ODATEDW | 104.000567 | 112.115237 | 90.361373 | 125.219806 | 150.570825 | 76.221898 | 149.026521 | 111.625652 |
| NUMCHLD | 1.547422 | 0.192972 | 0.000151 | 0.257288 | 0.042636 | 0.009868 | 0.022652 | 0.169453 |
| N_RDATE_7 | 612.000000 | 58.100211 | 612.000000 | 557.402129 | 612.000000 | 612.000000 | 612.000000 | 612.000000 |
| RAMNT_7 | 0.000000 | 15.528080 | 0.000000 | 1.465988 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| FEDGOV | 3.555581 | 3.006830 | 4.169974 | 3.155484 | 2.787692 | 2.612548 | 2.855621 | 3.070617 |
| VIETVETS | 33.823116 | 29.783807 | 39.723501 | 30.317446 | 26.877656 | 25.301064 | 28.060163 | 29.800990 |
| N_ADATE_7 | 61.061530 | 59.409661 | 59.434025 | 105.622397 | 67.086680 | 59.129004 | 59.064985 | 612.000000 |
| MBBOOKS | 0.558527 | 0.430274 | 0.478914 | 2.495604 | 0.473487 | 0.332433 | 0.518587 | 0.409255 |
| MBGARDEN | 0.000000 | 0.000000 | 0.000000 | 1.106432 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| N_FISTDATE | 101.204419 | 108.312058 | 88.812448 | 120.300787 | 143.637796 | 75.924141 | 142.148248 | 108.038251 |
| MAXRAMNT | 19.600871 | 18.179142 | 21.064434 | 18.670292 | 13.897335 | 20.003007 | 26.476292 | 19.452098 |
| N_LASTDATE | 62.227309 | 57.803303 | 62.071369 | 61.226284 | 59.789301 | 61.696290 | 63.795346 | 60.200214 |
| N_MAXRDATE | 70.060170 | 72.558053 | 66.771935 | 75.725590 | 84.240062 | 64.276697 | 82.526213 | 71.298783 |
| CARDPROM | 16.456431 | 17.682975 | 14.014032 | 20.259602 | 25.823155 | 10.637797 | 25.332604 | 15.893139 |
#Call UMAP to plot K-Prototypes Clustering
embedding_kproto=apply_umap(kproto_data)
plot_cluster_umap(embedding_kproto,kproto_labels,3,'Cluster')
#Instantiate the clustering model and visualizer
view=InterclusterDistance(KMeans(8,random_state=4))
#Fit the data to the visualizer
view.fit(embedding_kproto)
#Render the figure
view.show()
plt.show()
Validating the quality of clusters by treating them as labels and building a classification model on top. If the clusters are of high quality, the classification model will be able to predict them with high accuracy. At the same time, the models should use a variety of features to ensure that the clusters are not too simplistic.
LightGBM will be used as classifier as it can use categorical features
#Set LGBM Dataframe
lgbm_data=cluster_data.copy()
for i in lgbm_data.select_dtypes(include='object'):
lgbm_data[i]=lgbm_data[i].astype('category')
#Kmeans Clusters
clf_km=LGBMClassifier(colsample_by_tree=0.8)
cv_scores_km=cross_val_score(clf_km, lgbm_data, kmeans_labels, scoring='f1_weighted')
print(f'CV F1 score for K-Means clusters is {np.mean(cv_scores_km)}')
[LightGBM] [Warning] Unknown parameter: colsample_by_tree [LightGBM] [Warning] Unknown parameter: colsample_by_tree [LightGBM] [Warning] Unknown parameter: colsample_by_tree [LightGBM] [Warning] Unknown parameter: colsample_by_tree [LightGBM] [Warning] Unknown parameter: colsample_by_tree CV F1 score for K-Means clusters is 0.9738166796974144
clf_km.fit(lgbm_data, kmeans_labels)
explainer_km=shap.TreeExplainer(clf_km)
shap_values_km=explainer_km.shap_values(lgbm_data)
[LightGBM] [Warning] Unknown parameter: colsample_by_tree
shap.summary_plot(shap_values_km, lgbm_data, plot_type='bar', plot_size=(15, 10))
clf_kp = LGBMClassifier(colsample_by_tree=0.8)
cv_scores_kp = cross_val_score(clf_kp, lgbm_data, kproto_labels, scoring='f1_weighted')
print(f'CV F1 score for K-Prototypes clusters is {np.mean(cv_scores_kp)}')
[LightGBM] [Warning] Unknown parameter: colsample_by_tree [LightGBM] [Warning] Unknown parameter: colsample_by_tree [LightGBM] [Warning] Unknown parameter: colsample_by_tree [LightGBM] [Warning] Unknown parameter: colsample_by_tree [LightGBM] [Warning] Unknown parameter: colsample_by_tree CV F1 score for K-Prototypes clusters is 0.9737783305848711
clf_kp.fit(lgbm_data, kproto_labels)
explainer_kp = shap.TreeExplainer(clf_kp)
shap_values_kp = explainer_kp.shap_values(lgbm_data)
[LightGBM] [Warning] Unknown parameter: colsample_by_tree
shap.summary_plot(shap_values_kp, lgbm_data, plot_type='bar', plot_size=(15, 10))
Classifiers for both of the clustering methods have F1 score close to 1 which means that K-Means and K-prototypes have produced clusters that are easily distinguishable. Yet, to classify the K-Prototypes correctly, LightGBM uses more features, and some of the categorical features become important. This is in contrast to K-Means which could have been almost perfectly classified using just 15-18 features. This proves that the clusters produced by K-Prototypes are more informative.
We have only 2 categorical features with limited data values (4 and 2), so we can do encoding here to further utilization of the full list of features upfront
cluster_data_enc=cluster_data.copy()
# columns for categorical features
{item: cluster_data_enc[item].unique() for item in cluster_data_enc if (cluster_data_enc[item].dtype=='object') }
{'RFA_2A': array(['E', 'G', 'F', 'D'], dtype=object),
'PETS': array([' ', 'Y'], dtype=object)}
exch_dict = {'RFA_2A': {'D': '1', 'E': '2', 'F': '3', 'G': '4'},'PETS': {' ': '0', 'Y': '1'}}
for item in exch_dict.keys():
exch_map = exch_dict[item]
cluster_data_enc[item] = cluster_data_enc[item].map(exch_map)
cluster_data_enc[item] = cluster_data_enc[item].astype('int64', copy=False)
def get_r2_hc(df, link, max_nclus, min_nclus=1, dist='euclidean'):
def get_ss(matrix):
mc = matrix - matrix.mean(axis=0)
return (mc.T@mc).trace() #return sum of squares of matrix
matrix = df.values
ncols = matrix.shape[1]
sst = get_ss(matrix) #get total sum of squares
r2 = np.array([]) #where we will store the R2 metrics
for i in range(min_nclus, max_nclus+1):
Hclustering = AgglomerativeClustering(n_clusters=i, affinity=dist, linkage=link)
hclabels = Hclustering.fit_predict(matrix) #get cluster labels
concat = np.concatenate((matrix, np.expand_dims(hclabels,1)), axis=1)
ssw = np.array([get_ss(concat[concat[:,ncols]==j, :ncols]) for j in range(i)]).sum() #calculate ssw for a given cluster solution
r2 = np.append(r2, (sst-ssw)/sst) #save the R2 of the given cluster solution
return r2
def plot_r2_hc(df, labels):
#Getting the centroids of each cluster given by the K-means
df_clusters = df.groupby(labels).mean()
#Prepare input
hc_methods = ['ward', 'complete', 'average', 'single']
# Function defined above to obtain the R2 statistic
r2_hc_methods = pd.DataFrame(data=np.concatenate([np.expand_dims(get_r2_hc(df=df_clusters, link=i, max_nclus=10), 1) for i in hc_methods], axis=1),
index=range(1,10+1), columns=hc_methods)
#Plot data
sns.set()
fig = plt.figure(figsize=(15,7))
sns.lineplot(data=r2_hc_methods, linewidth=2.5, markers=['o']*4)
#Finalize the plot
fig.suptitle('R2 plot for various hierarchical methods', fontsize=23)
plt.gca().invert_xaxis()
plt.legend(title='HC methods', title_fontsize=13)
plt.xlabel('Number of clusters', fontsize=13)
plt.ylabel('R2', fontsize=13)
plt.show()
def plot_hc_dendogram(df, HCM):
#Hierarchical clustering assessment using scipy
z = linkage(df, method=HCM)
fig = plt.figure(figsize=(22,10))
#Set Dendrogram
set_link_color_palette(list(sns.color_palette().as_hex()))
dendrogram(z, color_threshold=8, truncate_mode='level', orientation='top', no_labels=True, above_threshold_color='k')
#Plot Dendrogram
plt.hlines(9.5, 0, 1000, colors='r', linestyles='dashed')
plt.title('Hierarchical Clustering - Ward\'s Dendrogram', fontsize=40)
plt.xlabel('K-means Units', fontsize=13)
plt.ylabel('Euclidean Distance', fontsize=13)
plt.show()
model = KMeans(100,random_state=4)
model.fit(kmeans_data)
clust_labels = model.predict(kmeans_data)
kmeans_clusters = kmeans_data.copy()
kmeans_clusters['kmeans_labels'] = clust_labels
plot_r2_hc(kmeans_clusters,'kmeans_labels')
From the graph above R2 for hierarchical clustering we can conclude that the best HCM method is ward hence this will be taken for the upcoming analysis
#updating the centroids of kmeans cluster given by the mean
kmeans_clusters = kmeans_clusters.groupby('kmeans_labels').mean()
plot_hc_dendogram(kmeans_clusters,'ward')
#Hierarchical clustering with sklearn and selected linkage and n_cluster according to plot above and below
Hclustering = AgglomerativeClustering(linkage='ward')
#K-Elbow Plots
kelbowplots(Hclustering, kmeans_clusters)
# Storing average silhouette metric
avg_silhouette = []
for nclus in range(1, 11):
# Skip cluster=1
if nclus == 1: continue
# Create a figure
fig = plt.figure(figsize=(13, 7))
# Initialize the KMeans object with n_clusters value and a random generator
kmclust = KMeans(n_clusters=nclus, init='k-means++', n_init=15, random_state=4)
cluster_labels = kmclust.fit_predict(kmeans_data)
# The silhouette_score gives the average value for all the samples.
# This gives a perspective into the density and separation of the formed clusters
silhouette_avg = silhouette_score(kmeans_data, cluster_labels)
avg_silhouette.append(silhouette_avg)
print(f'For n_clusters = {nclus}, the average silhouette_score is : {silhouette_avg}')
# Compute the silhouette scores for each sample
sample_silhouette_values = silhouette_samples(kmeans_data, cluster_labels)
y_lower = 10
for i in range(nclus):
# Aggregate the silhouette scores for samples belonging to cluster i, and sort them
ith_cluster_silhouette_values = sample_silhouette_values[cluster_labels == i]
ith_cluster_silhouette_values.sort()
# Get y_upper to demarcate silhouette y range size
size_cluster_i = ith_cluster_silhouette_values.shape[0]
y_upper = y_lower + size_cluster_i
# Filling the silhouette
color = cm.nipy_spectral(float(i) / nclus)
plt.fill_betweenx(np.arange(y_lower, y_upper),
0, ith_cluster_silhouette_values,
facecolor=color, edgecolor=color, alpha=0.7)
# Label the silhouette plots with their cluster numbers at the middle
plt.text(-0.05, y_lower + 0.5 * size_cluster_i, str(i))
# Compute the new y_lower for next plot
y_lower = y_upper + 10 # 10 for the 0 samples
plt.title('The silhouette plot for the various clusters')
plt.xlabel('The silhouette coefficient values')
plt.ylabel('Cluster label')
# The vertical line for average silhouette score of all the values
plt.axvline(x=silhouette_avg, color='red', linestyle='--')
# The silhouette coefficient can range from -1, 1
xmin, xmax = np.round(sample_silhouette_values.min() -0.1, 2), np.round(sample_silhouette_values.max() + 0.1, 2)
plt.xlim([xmin, xmax])
# The (nclus+1)*10 is for inserting blank space between silhouette
# plots of individual clusters, to demarcate them clearly.
plt.ylim([0, len(kmeans_data) + (nclus + 1) * 10])
plt.yticks([]) # Clear the yaxis labels / ticks
plt.xticks(np.arange(xmin, xmax, 0.1))
For n_clusters = 2, the average silhouette_score is : 0.12725164424128024 For n_clusters = 3, the average silhouette_score is : 0.1451332518699581 For n_clusters = 4, the average silhouette_score is : 0.14702776965334657 For n_clusters = 5, the average silhouette_score is : 0.12591907333505317 For n_clusters = 6, the average silhouette_score is : 0.11195789341728894 For n_clusters = 7, the average silhouette_score is : 0.10231748054830442 For n_clusters = 8, the average silhouette_score is : 0.10525856208877543 For n_clusters = 9, the average silhouette_score is : 0.10109064917279584 For n_clusters = 10, the average silhouette_score is : 0.09961330996471655
def silhouette_analysis(df, estimator, shape, figsize, max_nclus, min_nclus=2, dist="euclidean"):
"""
This function calculates the silhouette coefficient for each observation according to a clustering solution and then builds the
Silhouette plots for a given range of cluster solutions. This is useful to find out the most appropriate number of clusters.
"""
range_n_clusters = list(range(min_nclus, max_nclus+1))
sns.set()
fig, axes = plt.subplots(nrows=shape[0], ncols=shape[1], figsize=figsize)
if len(range_n_clusters)==1: # in case we want to seed the silhouette for just one cluster solution
forax = [axes]
else:
forax = axes.flatten()
for ax, n_clusters in zip(forax, range_n_clusters):
# Get parameter that defines number of clusters
if 'n_clusters' in estimator.get_params():
param = 'n_clusters'
elif 'n_components' in estimator.get_params():
param = 'n_components'
else:
print('Estimator has no parameter to define number of clusters')
return None
# Get the cluster labels by applying a given clustering algorithm
clustering = estimator.set_params(**{param:n_clusters})
labels = clustering.fit_predict(df)
# The silhouette_score gives the average value for all the samples.
# This gives a perspective into the density and separation of the formed clusters
silhouette_avg = silhouette_score(df, labels, metric=dist)
# Compute the silhouette scores for each sample
sample_silhouette_values = silhouette_samples(df, labels, metric=dist)
# The silhouette coefficient can range from -1, 1
ax.set_xlim([sample_silhouette_values.min()-0.1, 1])
# The (n_clusters+1)*10 is for inserting blank space between silhouette plots of individual clusters, to demarcate them clearly.
ax.set_ylim([0, df.shape[0] + (n_clusters + 1) * 10])
y_lower = 10 # initialize y_lower
for i in range(n_clusters):
# Aggregate the silhouette scores for samples belonging to cluster i, and sort them
ith_cluster_silhouette_values = sample_silhouette_values[labels == i]
ith_cluster_silhouette_values.sort()
size_cluster_i = ith_cluster_silhouette_values.shape[0]
y_upper = y_lower + size_cluster_i
color = cm.nipy_spectral(float(i) / n_clusters)
ax.fill_betweenx(np.arange(y_lower, y_upper),
0, ith_cluster_silhouette_values,
facecolor=color, edgecolor=color, alpha=0.7)
# Label the silhouette plots with their cluster numbers at the middle
ax.text(-0.05, y_lower + 0.5 * size_cluster_i, str(i))
# Compute the new y_lower for next plot
y_lower = y_upper + 10 # 10 for the 0 samples
ax.set_title('{} Clusters'.format(n_clusters), fontsize=13)
ax.set_xlabel('Silhouette Coefficients')
ax.set_ylabel('Cluster Labels')
ax.set_yticks([]) # Clear the yaxis labels / ticks
ax.axvline(x=silhouette_avg, color='red', linestyle='--', label='Average Silhouette') #The vertical line for average silhouette score of all the values
handles, _ = ax.get_legend_handles_labels()
ax.legend(handles, ['Average Silhouette = {0:.2f}'.format(silhouette_avg)])
plt.subplots_adjust(hspace=0.35)
plt.suptitle(('Clustering Silhouette Plots'), fontsize=23, fontweight='bold')
plt.show()
from sompy.sompy import SOMFactory
#Producing SOM clustering
sm = SOMFactory().build(data=kmeans_data.values, mapsize=(10,10), normalization='var', initialization='random',
component_names=kmeans_data.columns, lattice='hexa', training='seq')
sm.train(n_job=4, verbose=None, train_rough_len=100, train_finetune_len=100)
#Obtaining SOM's BMUs labels
som_std_df = pd.DataFrame(np.concatenate((sm._data, np.expand_dims(sm._bmu[0],1)), axis=1),
index=kmeans_data.index, columns=np.append(kmeans_data.columns,'labels_som'))
print('SOM quantization error: {0:.3f}'.format(sm.calculate_quantization_error()))
SOM quantization error: 0.522
from sompy.visualization.mapview import View2D
#Visualizing the component plates (feature values)
view2D = View2D(10,10,'Component Plates', text_size=10)
view2D.show(sm, col_sz=5, what='codebook')
plt.subplots_adjust(top=0.90)
plt.show()
plot_r2_hc(som_std_df,'labels_som')
From the graph above R2 for hierarchical clustering we can conclude that the best HCM method is ward hence this will be taken for the upcoming analysis
# Update the centroids of som units given by the BMUs of each observation
som_units = som_std_df.groupby('labels_som').mean()
plot_hc_dendogram(som_units,'ward')
# Hierarchical clustering with sklearn and selected linkage and n_cluster according to plot above and below
Hclustering = AgglomerativeClustering(linkage='ward')
# K-elbow plots
kelbowplots(Hclustering, som_units)
# Function defined above
estimator = AgglomerativeClustering(affinity='euclidean', linkage='ward')
silhouette_analysis(som_units, estimator, (3,3), (20, 11), 10)
from sompy.visualization.hitmap import HitMapView
# Perform K-Means clustering on top of the 100 untis (sm.get_node_vectors() output)
kmeans = KMeans(n_clusters=6, init='k-means++', n_init=20, random_state=4)
nodeclus_labels = sm.cluster(kmeans)
hits = HitMapView(12, 12,'Clustering', text_size=10)
hits.show(sm, anotate=True, onlyzeros=False, labelsize=7, cmap='Pastel1')
plt.show()
def cluster_profiles(df, label_columns, figsize, compar_titles=None):
"""
Pass df with labels columns of one or multiple clustering labels.
Then specify this label columns to perform the cluster profile according to them.
"""
if compar_titles == None:
compar_titles = ['']*len(label_columns)
sns.set()
fig, axes = plt.subplots(nrows=len(label_columns), ncols=2, figsize=figsize, squeeze=False)
for ax, label, titl in zip(axes, label_columns, compar_titles):
# Filtering df
drop_cols = [i for i in label_columns if i!=label]
dfax = df.drop(drop_cols, axis=1)
# Getting the cluster centroids and counts
centroids = dfax.groupby(by=label, as_index=False).mean()
counts = dfax.groupby(by=label, as_index=False).count().iloc[:,[0,1]]
counts.columns = [label, 'counts']
# Setting Data
pd.plotting.parallel_coordinates(centroids, label, color=sns.color_palette(), ax=ax[0])
sns.barplot(x=label, y='counts', data=counts, ax=ax[1])
#Setting Layout
handles, _ = ax[0].get_legend_handles_labels()
cluster_labels = ['Cluster {}'.format(i) for i in range(len(handles))]
ax[0].annotate(s=titl, xy=(0.95,1.1), xycoords='axes fraction', fontsize=10, fontweight = 'heavy')
ax[0].legend(handles, cluster_labels) # Adaptable to number of clusters
ax[0].axhline(color="black", linestyle='--')
ax[0].set_title('Cluster Means - {} Clusters'.format(len(handles)), fontsize=13)
ax[0].set_xticklabels(ax[0].get_xticklabels(), rotation=-90)
ax[1].set_xticklabels(cluster_labels)
ax[1].set_xlabel('')
ax[1].set_ylabel('Absolute Frequency')
ax[1].set_title('Cluster Sizes - {} Clusters'.format(len(handles)), fontsize=13)
plt.subplots_adjust(hspace=0.4, top=0.90)
plt.suptitle('Cluster Simple Profilling', fontsize=23)
plt.show()
# Defining numbers of clusters
CLUSN = 8
# Hierarchical Clustering with sklearn
estimator = AgglomerativeClustering(n_clusters=CLUSN, linkage='ward')
labels = estimator.fit_predict(som_units)
# Getting the HC labels for each SOM Unit
som_units_hc = pd.DataFrame(np.concatenate((som_units.values, np.expand_dims(labels,1)), axis=1),
index=som_units.index, columns=np.append(som_units.columns,['labels_som_hc_8']))
# Getting the HC labels for each observation in the main dataframe
som_hc_std_df = som_std_df.merge(right=som_units_hc.loc[:,'labels_som_hc_8'],
left_on='labels_som', right_index=True).sort_index()
# Cluster Simple Profilling
cluster_profiles(som_hc_std_df.drop('labels_som', axis=1), ['labels_som_hc_8'], (23, 7))
# Hierarchical clustering with sklearn and selected linkage and n_cluster according to plot above and below
Kmeans = KMeans(random_state=4)
# K-elbow plots
kelbowplots(Kmeans, som_units)
# Function defined above
estimator = KMeans(random_state=4)
silhouette_analysis(som_units, estimator, (3,3), (20, 11), 10)
# Defining numbers of clusters
CLUSN = 8
# KMeans with sklearn
estimator = KMeans(n_clusters=CLUSN)
labels = estimator.fit_predict(som_units)
# Getting the KMeans labels for each SOM Unit
som_units_hc = pd.DataFrame(np.concatenate((som_units.values, np.expand_dims(labels,1)), axis=1),
index=som_units.index, columns=np.append(som_units.columns,['labels_som_kmeans_8']))
# Getting the KMeans labels for each observation in the main dataframe
som_kmeans_df = som_std_df.merge(right=som_units_hc.loc[:,'labels_som_kmeans_8'],
left_on='labels_som', right_index=True).sort_index()
# Cluster simple profilling
cluster_profiles(som_kmeans_df.drop('labels_som', axis=1), ['labels_som_kmeans_8'], (25, 7))
# Function defined above
estimator = GaussianMixture(random_state=random_state, n_init=10)
silhouette_analysis(kmeans_data, estimator, (3,3), (20, 11), 10)
# Selecting number of components based on AIC and BIC
n_components = np.arange(1, 16)
models = [GaussianMixture(n, covariance_type='full', n_init=10, random_state=4).fit(kmeans_data) for n in n_components]
bic_values = [m.bic(kmeans_data) for m in models]
aic_values = [m.aic(kmeans_data) for m in models]
plt.plot(n_components, bic_values, label='BIC')
plt.plot(n_components, aic_values, label='AIC')
plt.legend(loc='best')
plt.xlabel('n_components')
plt.xticks(n_components)
plt.show()
# Performing GMM Clustering
gmm = GaussianMixture(n_components=8, covariance_type='full', n_init=10, init_params='kmeans', random_state=random_state)
gmm_labels = gmm.fit_predict(kmeans_data)
# Concatenating the labels to df
df_concat = kmeans_data.copy()
df_concat.drop(['labels'],axis=1,inplace=True)
df_concat['gmm_labels']=gmm_labels
df_concat.head()
| RFA_2F | IC3 | HHD2 | ETHC3 | INCOME | AGE | N_ODATEDW | NUMCHLD | N_RDATE_7 | RAMNT_7 | FEDGOV | VIETVETS | N_ADATE_7 | MBBOOKS | MBGARDEN | N_FISTDATE | MAXRAMNT | N_LASTDATE | N_MAXRDATE | CARDPROM | gmm_labels | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| index | |||||||||||||||||||||
| 0 | 1.522953 | -0.174613 | 0.574399 | 0.840312 | 0.089928 | 0.040448 | 0.783487 | -0.389658 | 0.316734 | -0.316734 | -0.490916 | 0.311415 | -0.325295 | -0.537481 | -0.156262 | 0.701996 | -0.821522 | -0.169728 | 1.048083 | 1.000048 | 4 |
| 1 | 0.533260 | 3.320908 | 2.160054 | -1.307435 | 1.237351 | -0.989092 | -0.678759 | 2.563324 | 0.316734 | -0.316734 | -0.490916 | 1.602509 | -0.325295 | 1.948978 | -0.156262 | -0.548924 | 0.796598 | -0.169728 | -0.851874 | -0.691395 | 0 |
| 2 | 1.522953 | -0.571581 | 0.190568 | 0.273252 | -0.509019 | 0.475543 | 0.539863 | -0.389658 | 0.316734 | -0.316734 | -0.490916 | -0.013475 | -0.325295 | 1.770134 | -0.156262 | 0.657284 | -0.150895 | -0.169728 | 1.588623 | 0.900036 | 4 |
| 3 | 1.522953 | 0.132271 | -0.078019 | -0.216435 | -1.786459 | 0.697636 | 1.222403 | -0.389658 | 0.316734 | -0.316734 | 0.424410 | -1.054447 | -0.325295 | -0.537481 | -0.156262 | 1.366294 | -1.033431 | -0.169728 | 0.547991 | 1.000048 | 4 |
| 4 | 0.533260 | -0.564346 | 0.777560 | -2.712723 | -0.509019 | 1.303874 | 1.421905 | 2.563324 | 0.316734 | -0.316734 | 0.055083 | -1.436767 | 0.201975 | 1.963492 | -0.156262 | 2.783013 | -0.297283 | -0.422134 | -1.017231 | 2.455224 | 0 |
def get_ss(df):
"""Computes the sum of squares for all variables given a dataset
"""
ss = np.sum(df.var() * (df.count() - 1))
return ss # return sum of sum of squares of each df variable
# Computing the R^2 of the cluster solution
sst = get_ss(cluster_data_enc) # get total sum of squares
ssw_labels = df_concat.groupby(by='gmm_labels').apply(get_ss) # compute ssw for each cluster labels
ssb = sst - np.sum(ssw_labels) # remember: SST = SSW + SSB
r2 = ssb / sst
print("Cluster Solution with R^2 of %0.4f" % r2)
Cluster Solution with R^2 of 0.9998
# Perform DBSCAN clustering
dbscan = DBSCAN(eps=1.9, min_samples=20, n_jobs=4)
dbscan_labels = dbscan.fit_predict(kmeans_data)
dbscan_n_clusters = len(np.unique(dbscan_labels))
print('Number of estimated clusters : %d' % dbscan_n_clusters)
Number of estimated clusters : 14
df_concat
| RFA_2F | IC3 | HHD2 | ETHC3 | INCOME | AGE | N_ODATEDW | NUMCHLD | N_RDATE_7 | RAMNT_7 | FEDGOV | VIETVETS | N_ADATE_7 | MBBOOKS | MBGARDEN | N_FISTDATE | MAXRAMNT | N_LASTDATE | N_MAXRDATE | CARDPROM | labels | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| index | |||||||||||||||||||||
| 0 | 1.522953 | -0.174613 | 0.574399 | 0.840312 | 0.089928 | 0.040448 | 0.783487 | -0.389658 | 0.316734 | -0.316734 | -0.490916 | 0.311415 | -0.325295 | -0.537481 | -0.156262 | 0.701996 | -0.821522 | -0.169728 | 1.048083 | 1.000048 | 1 |
| 1 | 0.533260 | 3.320908 | 2.160054 | -1.307435 | 1.237351 | -0.989092 | -0.678759 | 2.563324 | 0.316734 | -0.316734 | -0.490916 | 1.602509 | -0.325295 | 1.948978 | -0.156262 | -0.548924 | 0.796598 | -0.169728 | -0.851874 | -0.691395 | 3 |
| 2 | 1.522953 | -0.571581 | 0.190568 | 0.273252 | -0.509019 | 0.475543 | 0.539863 | -0.389658 | 0.316734 | -0.316734 | -0.490916 | -0.013475 | -0.325295 | 1.770134 | -0.156262 | 0.657284 | -0.150895 | -0.169728 | 1.588623 | 0.900036 | 1 |
| 3 | 1.522953 | 0.132271 | -0.078019 | -0.216435 | -1.786459 | 0.697636 | 1.222403 | -0.389658 | 0.316734 | -0.316734 | 0.424410 | -1.054447 | -0.325295 | -0.537481 | -0.156262 | 1.366294 | -1.033431 | -0.169728 | 0.547991 | 1.000048 | 1 |
| 4 | 0.533260 | -0.564346 | 0.777560 | -2.712723 | -0.509019 | 1.303874 | 1.421905 | 2.563324 | 0.316734 | -0.316734 | 0.055083 | -1.436767 | 0.201975 | 1.963492 | -0.156262 | 2.783013 | -0.297283 | -0.422134 | -1.017231 | 2.455224 | 1 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 95407 | -0.942374 | 0.754786 | -0.163943 | -1.307435 | 0.089928 | -0.381838 | -1.536071 | -0.389658 | -3.157219 | 3.157590 | 1.872670 | 1.122414 | -0.048911 | -0.537481 | -0.156262 | -1.615662 | 0.796598 | -0.666757 | -1.194650 | -1.569204 | 4 |
| 95408 | -0.942374 | 2.322588 | 1.549322 | -1.307435 | 1.791649 | -0.857021 | -1.536071 | 2.563324 | -3.157224 | 3.157583 | -1.497847 | 0.877368 | -0.048911 | 1.770134 | -0.156262 | -1.661370 | 0.336979 | -0.903714 | -1.385235 | -1.920456 | 4 |
| 95409 | 1.175084 | -0.379779 | -0.788290 | -0.326785 | 0.089928 | -0.030847 | -1.076732 | -0.389658 | 0.316734 | -0.316734 | -1.497847 | 1.061487 | 3.224795 | -0.537481 | -0.156262 | -0.963013 | -1.270249 | -2.357552 | 0.398518 | -0.434798 | 0 |
| 95410 | 1.522953 | 1.141325 | 1.096633 | 0.088156 | 1.791649 | -0.172353 | 1.421905 | -0.389658 | 0.316734 | -0.316734 | -0.490916 | 0.375418 | -0.325295 | -0.537481 | -0.156262 | 1.402739 | 0.439878 | -2.877328 | -2.583779 | 1.847800 | 3 |
| 95411 | -0.942374 | 0.754786 | 1.549322 | -0.442467 | 0.670904 | 1.458485 | 1.010221 | -0.389658 | 0.316734 | -0.316734 | 0.424410 | -0.484478 | -0.325295 | -0.537481 | -0.156262 | 1.119632 | 3.887751 | -2.710603 | 1.130502 | 1.481660 | 1 |
90662 rows × 21 columns
# Concatenating the labels to df
df_concat = kmeans_data.copy()
df_concat.drop(['labels'],axis=1,inplace=True)
df_concat['dbscan_labels']=dbscan_labels
df_concat.head()
| RFA_2F | IC3 | HHD2 | ETHC3 | INCOME | AGE | N_ODATEDW | NUMCHLD | N_RDATE_7 | RAMNT_7 | FEDGOV | VIETVETS | N_ADATE_7 | MBBOOKS | MBGARDEN | N_FISTDATE | MAXRAMNT | N_LASTDATE | N_MAXRDATE | CARDPROM | dbscan_labels | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| index | |||||||||||||||||||||
| 0 | 1.522953 | -0.174613 | 0.574399 | 0.840312 | 0.089928 | 0.040448 | 0.783487 | -0.389658 | 0.316734 | -0.316734 | -0.490916 | 0.311415 | -0.325295 | -0.537481 | -0.156262 | 0.701996 | -0.821522 | -0.169728 | 1.048083 | 1.000048 | 0 |
| 1 | 0.533260 | 3.320908 | 2.160054 | -1.307435 | 1.237351 | -0.989092 | -0.678759 | 2.563324 | 0.316734 | -0.316734 | -0.490916 | 1.602509 | -0.325295 | 1.948978 | -0.156262 | -0.548924 | 0.796598 | -0.169728 | -0.851874 | -0.691395 | -1 |
| 2 | 1.522953 | -0.571581 | 0.190568 | 0.273252 | -0.509019 | 0.475543 | 0.539863 | -0.389658 | 0.316734 | -0.316734 | -0.490916 | -0.013475 | -0.325295 | 1.770134 | -0.156262 | 0.657284 | -0.150895 | -0.169728 | 1.588623 | 0.900036 | 1 |
| 3 | 1.522953 | 0.132271 | -0.078019 | -0.216435 | -1.786459 | 0.697636 | 1.222403 | -0.389658 | 0.316734 | -0.316734 | 0.424410 | -1.054447 | -0.325295 | -0.537481 | -0.156262 | 1.366294 | -1.033431 | -0.169728 | 0.547991 | 1.000048 | 0 |
| 4 | 0.533260 | -0.564346 | 0.777560 | -2.712723 | -0.509019 | 1.303874 | 1.421905 | 2.563324 | 0.316734 | -0.316734 | 0.055083 | -1.436767 | 0.201975 | 1.963492 | -0.156262 | 2.783013 | -0.297283 | -0.422134 | -1.017231 | 2.455224 | -1 |
# Detecting noise (potential outliers)
df_concat.loc[df_concat['dbscan_labels'] == -1]
| RFA_2F | IC3 | HHD2 | ETHC3 | INCOME | AGE | N_ODATEDW | NUMCHLD | N_RDATE_7 | RAMNT_7 | FEDGOV | VIETVETS | N_ADATE_7 | MBBOOKS | MBGARDEN | N_FISTDATE | MAXRAMNT | N_LASTDATE | N_MAXRDATE | CARDPROM | dbscan_labels | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| index | |||||||||||||||||||||
| 1 | 0.533260 | 3.320908 | 2.160054 | -1.307435 | 1.237351 | -0.989092 | -0.678759 | 2.563324 | 0.316734 | -0.316734 | -0.490916 | 1.602509 | -0.325295 | 1.948978 | -0.156262 | -0.548924 | 0.796598 | -0.169728 | -0.851874 | -0.691395 | -1 |
| 4 | 0.533260 | -0.564346 | 0.777560 | -2.712723 | -0.509019 | 1.303874 | 1.421905 | 2.563324 | 0.316734 | -0.316734 | 0.055083 | -1.436767 | 0.201975 | 1.963492 | -0.156262 | 2.783013 | -0.297283 | -0.422134 | -1.017231 | 2.455224 | -1 |
| 11 | 0.533260 | -0.741015 | -2.499743 | 1.054471 | -1.786459 | 1.074211 | -1.536071 | -0.389658 | 0.316734 | -0.316734 | -1.497847 | -1.054447 | -0.325295 | 1.770134 | -0.156262 | -1.396725 | -0.297283 | -0.169728 | -0.418695 | -1.253594 | -1 |
| 12 | 1.522953 | -0.756035 | 0.574399 | 0.182280 | 0.089928 | 0.847319 | 0.783487 | 2.571393 | 0.316734 | -0.316734 | 1.102284 | 0.117503 | 3.224795 | 1.770134 | 6.399510 | 0.832713 | -2.197544 | -0.422134 | 1.811821 | 0.377794 | -1 |
| 13 | -0.942374 | -0.134495 | 0.777560 | -0.692949 | 0.089928 | -0.030847 | -0.010801 | -0.389658 | 0.316734 | -0.316734 | -0.490916 | 0.502532 | -0.325295 | -0.537481 | -0.156262 | -0.181905 | 2.050775 | -2.710603 | 0.475423 | 0.591455 | -1 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 95398 | 1.175084 | 0.823575 | -0.330457 | -0.110814 | 0.670904 | 2.008765 | 1.421905 | -0.389658 | 0.316734 | -0.316734 | -1.497847 | -0.553614 | -0.325295 | -0.537481 | -0.156262 | 1.197409 | 0.796598 | -0.666757 | -0.697585 | 1.196213 | -1 |
| 95408 | -0.942374 | 2.322588 | 1.549322 | -1.307435 | 1.791649 | -0.857021 | -1.536071 | 2.563324 | -3.157224 | 3.157583 | -1.497847 | 0.877368 | -0.048911 | 1.770134 | -0.156262 | -1.661370 | 0.336979 | -0.903714 | -1.385235 | -1.920456 | -1 |
| 95409 | 1.175084 | -0.379779 | -0.788290 | -0.326785 | 0.089928 | -0.030847 | -1.076732 | -0.389658 | 0.316734 | -0.316734 | -1.497847 | 1.061487 | 3.224795 | -0.537481 | -0.156262 | -0.963013 | -1.270249 | -2.357552 | 0.398518 | -0.434798 | -1 |
| 95410 | 1.522953 | 1.141325 | 1.096633 | 0.088156 | 1.791649 | -0.172353 | 1.421905 | -0.389658 | 0.316734 | -0.316734 | -0.490916 | 0.375418 | -0.325295 | -0.537481 | -0.156262 | 1.402739 | 0.439878 | -2.877328 | -2.583779 | 1.847800 | -1 |
| 95411 | -0.942374 | 0.754786 | 1.549322 | -0.442467 | 0.670904 | 1.458485 | 1.010221 | -0.389658 | 0.316734 | -0.316734 | 0.424410 | -0.484478 | -0.325295 | -0.537481 | -0.156262 | 1.119632 | 3.887751 | -2.710603 | 1.130502 | 1.481660 | -1 |
31585 rows × 21 columns
# Computing the R^2 of the cluster solution
df_nonoise = df_concat.loc[df_concat['dbscan_labels'] != -1]
sst = get_ss(cluster_data_enc) # get total sum of squares
ssw_labels = df_nonoise.groupby(by='dbscan_labels').apply(get_ss) # compute ssw for each cluster labels
ssb = sst - np.sum(ssw_labels) # remember: SST = SSW + SSB
r2 = ssb / sst
print('Cluster solution with R^2 of %0.4f' % r2)
Cluster solution with R^2 of 0.9999
def cluster_metric_summary(cluster_model):
index_name=['Silhouette_Score','Calinski_Harabasz_Score','Davies_Bouldin_Score']
column_name = ['KM','KM+HC','HC+SOM','KM+SOM','GMM','DBSCAN']
df = pd.DataFrame(index=index_name, columns=column_name)
if column_name == 'DBSCAN': n_clusters = len(set(labels)) - (1 if -1 in labels else 0)
for i,model in enumerate(cluster_model):
cluster_labels = model[0].fit_predict(model[1])
df[column_name[i]][0] = silhouette_score(model[1],cluster_labels)
df[column_name[i]][1] = calinski_harabasz_score(model[1],cluster_labels)
df[column_name[i]][2] = davies_bouldin_score(model[1],cluster_labels)
return df
for n_clusters in range(5,11):
cluster_model=[]
cluster_model.append([KMeans(n_clusters=n_clusters, init='k-means++', max_iter=1000, tol=0.0001),kmeans_data])
cluster_model.append([AgglomerativeClustering(n_clusters=n_clusters, linkage='ward'),kmeans_clusters])
cluster_model.append([AgglomerativeClustering(n_clusters=n_clusters, linkage='ward'),som_units])
cluster_model.append([KMeans(n_clusters=n_clusters),som_units])
cluster_model.append([GaussianMixture(n_components=n_clusters, covariance_type='full', random_state=random_state), kmeans_data])
cluster_model.append([DBSCAN(eps=1.9, min_samples= 40, n_jobs=4), kmeans_data])
dic['cluster_metric_'+str(n_clusters)]=cluster_metric_summary(cluster_model)
# Print Clustering Accuracy Metrics - 5 Clusters
dic['cluster_metric_5']
| KM | KM+HC | HC+SOM | KM+SOM | GMM | DBSCAN | |
|---|---|---|---|---|---|---|
| Silhouette_Score | 0.123635 | 0.211798 | 0.223448 | 0.192365 | 0.0968578 | -0.10352 |
| Calinski_Harabasz_Score | 9844.72 | 21.3917 | 12.9446 | 12.8738 | 5323.15 | 1063.18 |
| Davies_Bouldin_Score | 2.08232 | 1.48007 | 1.38095 | 1.38171 | 2.716 | 2.50095 |
# Print Clustering Accuracy Metrics
dic['cluster_metric_6']
| KM | KM+HC | HC+SOM | KM+SOM | GMM | DBSCAN | |
|---|---|---|---|---|---|---|
| Silhouette_Score | 0.130104 | 0.237995 | 0.235647 | 0.196629 | 0.0895409 | -0.10352 |
| Calinski_Harabasz_Score | 9213.6 | 22.1867 | 13.1287 | 13.6484 | 6309.01 | 1063.18 |
| Davies_Bouldin_Score | 1.97074 | 1.33865 | 1.12042 | 1.19123 | 2.32194 | 2.50095 |
# Print Clustering Accuracy Metrics
dic['cluster_metric_7']
| KM | KM+HC | HC+SOM | KM+SOM | GMM | DBSCAN | |
|---|---|---|---|---|---|---|
| Silhouette_Score | 0.100278 | 0.237863 | 0.125975 | 0.180871 | 0.0874229 | -0.10352 |
| Calinski_Harabasz_Score | 8293.71 | 20.0488 | 13.2217 | 13.7969 | 5380.57 | 1063.18 |
| Davies_Bouldin_Score | 2.28326 | 1.1734 | 1.23103 | 1.14436 | 2.92833 | 2.50095 |
# Print Clustering Accuracy Metrics
dic['cluster_metric_8']
| KM | KM+HC | HC+SOM | KM+SOM | GMM | DBSCAN | |
|---|---|---|---|---|---|---|
| Silhouette_Score | 0.112416 | 0.189642 | 0.13388 | 0.157847 | 0.078439 | -0.10352 |
| Calinski_Harabasz_Score | 7733.77 | 18.4646 | 13.4774 | 13.1749 | 6182.16 | 1063.18 |
| Davies_Bouldin_Score | 2.05538 | 1.27619 | 1.20845 | 1.29503 | 2.47229 | 2.50095 |
# Print Clustering Accuracy Metrics
dic['cluster_metric_9']
| KM | KM+HC | HC+SOM | KM+SOM | GMM | DBSCAN | |
|---|---|---|---|---|---|---|
| Silhouette_Score | 0.101084 | 0.186222 | 0.155074 | 0.175582 | 0.0525386 | -0.10352 |
| Calinski_Harabasz_Score | 7549.5 | 17.2327 | 13.8247 | 14.6557 | 5138.1 | 1063.18 |
| Davies_Bouldin_Score | 2.13662 | 1.28227 | 1.19662 | 1.17261 | 2.99488 | 2.50095 |
# Print Clustering Accuracy Metrics
dic['cluster_metric_10']
| KM | KM+HC | HC+SOM | KM+SOM | GMM | DBSCAN | |
|---|---|---|---|---|---|---|
| Silhouette_Score | 0.0995755 | 0.190079 | 0.160387 | 0.190558 | 0.0748834 | -0.10352 |
| Calinski_Harabasz_Score | 7106.32 | 16.3174 | 14.2117 | 14.9236 | 4058.49 | 1063.18 |
| Davies_Bouldin_Score | 2.18049 | 1.18085 | 1.08338 | 1.02733 | 3.19851 | 2.50095 |
# Applying the right clustering algorithm and number of clusters
kmeans_final = KMeans(n_clusters=6, init='k-means++', n_init=20, random_state=42)
kmeans_final_labels = kmeans_final.fit_predict(kmeans_data)
kmeans_data['labels'] = kmeans_final_labels
# Re-running the Hierarchical clustering based on the correct number of clusters
hclust = AgglomerativeClustering(linkage='ward', affinity='euclidean', n_clusters=6)
hclust_labels = hclust.fit_predict(kmeans_clusters)
kmeans_clusters['hclust_labels'] = hclust_labels
kmeans_clusters # centroid's cluster labels
| RFA_2F | IC3 | HHD2 | ETHC3 | INCOME | AGE | N_ODATEDW | NUMCHLD | N_RDATE_7 | RAMNT_7 | FEDGOV | VIETVETS | N_ADATE_7 | MBBOOKS | MBGARDEN | N_FISTDATE | MAXRAMNT | N_LASTDATE | N_MAXRDATE | CARDPROM | hclust_labels | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| kmeans_labels | |||||||||||||||||||||
| 0 | 0.323792 | -0.455103 | -0.413878 | 0.538864 | -0.825714 | -1.830142 | 0.869785 | -0.389658 | 0.316734 | -0.316734 | -0.122324 | -0.261334 | -0.324370 | -0.400657 | -0.156262 | 0.877781 | -0.262282 | 0.045774 | 0.550193 | 0.862667 | 1 |
| 1 | 1.215165 | -0.504112 | -0.131712 | 0.057688 | -1.306707 | 0.611071 | -0.729506 | -0.389658 | 0.316734 | -0.316734 | 0.264725 | -0.010839 | -0.325295 | -0.537481 | -0.156262 | -0.725866 | -0.958919 | -0.258622 | -0.264923 | -0.566087 | 0 |
| 2 | 0.905534 | -0.027085 | 0.200142 | 0.041397 | 0.471505 | 0.188798 | 1.034968 | -0.389658 | 0.316734 | -0.316734 | 0.157325 | 0.045362 | -0.324192 | -0.533658 | -0.156262 | 1.030669 | -0.575015 | -0.250755 | -0.566038 | 0.915782 | 1 |
| 3 | -0.850736 | -0.487314 | 0.032036 | -0.184234 | -0.900881 | 0.080305 | 0.007665 | -0.389658 | 0.316734 | -0.316734 | -0.330400 | 0.028059 | -0.325295 | -0.535401 | -0.156262 | -0.008717 | 0.426886 | 1.719187 | 0.385859 | 0.009775 | 1 |
| 4 | -0.085891 | 0.770859 | 0.961292 | -0.801197 | 0.758452 | -0.402127 | -1.027120 | -0.389658 | 0.316734 | -0.316734 | 0.393130 | 0.820245 | -0.284374 | 1.849579 | -0.156262 | -1.018103 | 0.179910 | -0.215064 | -0.634988 | -0.956663 | 0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 95 | -0.076086 | -0.327965 | -0.172005 | 0.003315 | 0.031765 | -0.401084 | 0.623820 | 2.565990 | 0.316734 | -0.316734 | -0.098741 | -0.074623 | -0.324613 | -0.537481 | -0.156262 | 0.604654 | 0.337910 | -0.337309 | -0.529783 | 0.568123 | 2 |
| 96 | 1.102104 | 0.524680 | 0.926631 | -0.898173 | 0.619547 | -0.934855 | -0.589945 | 2.566954 | 0.316734 | -0.316734 | 0.677600 | 1.040395 | -0.323738 | -0.186426 | -0.156262 | -0.582188 | -0.639744 | -0.320570 | -0.295201 | -0.411986 | 2 |
| 97 | 1.210973 | -0.577966 | -0.368485 | 0.521703 | -0.930794 | 0.843617 | 1.086693 | -0.383237 | 0.316734 | -0.316734 | -0.206846 | -0.252208 | -0.323386 | -0.537481 | -0.156262 | 1.090726 | -1.787579 | -0.187709 | 1.399863 | 1.039217 | 1 |
| 98 | 1.246650 | -0.047222 | 0.193605 | -0.042003 | -0.251413 | 0.576147 | 1.042212 | -0.179338 | 0.316734 | -0.316734 | 0.180702 | 0.205948 | 3.224795 | -0.061037 | -0.156262 | 1.037584 | -1.350228 | -0.606661 | 0.975763 | 0.926914 | 4 |
| 99 | 0.820475 | -0.332276 | 0.320421 | -0.530221 | -0.786052 | 0.677171 | 1.012767 | -0.389658 | 0.316734 | -0.316734 | 0.750360 | 0.415996 | -0.324854 | -0.523449 | -0.156262 | 1.021322 | -0.287517 | -0.087773 | 1.244128 | 1.026164 | 1 |
100 rows × 21 columns
df_concat = cluster_data.copy()
df_concat['Cluster']=kmeans_final_labels
df_concat.head()
| RFA_2F | RFA_2A | IC3 | HHD2 | ETHC3 | INCOME | AGE | N_ODATEDW | NUMCHLD | PETS | N_RDATE_7 | RAMNT_7 | FEDGOV | VIETVETS | N_ADATE_7 | MBBOOKS | MBGARDEN | N_FISTDATE | MAXRAMNT | N_LASTDATE | N_MAXRDATE | CARDPROM | Cluster | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| index | |||||||||||||||||||||||
| 0 | 4 | E | 349 | 80 | 25 | 4.0 | 60.0 | 144 | 0.0 | 612 | 0.0 | 1 | 34 | 59 | 0.0 | 0.0 | 134 | 12.0 | 61 | 83 | 27 | 1 | |
| 1 | 2 | G | 1026 | 94 | 5 | 6.0 | 45.0 | 84 | 1.0 | 612 | 0.0 | 1 | 55 | 59 | 3.0 | 0.0 | 87 | 25.0 | 61 | 61 | 12 | 3 | |
| 2 | 4 | E | 292 | 76 | 18 | 3.0 | 66.0 | 132 | 0.0 | 612 | 0.0 | 1 | 29 | 59 | 1.0 | 0.0 | 132 | 16.0 | 61 | 102 | 26 | 1 | |
| 3 | 4 | E | 396 | 73 | 13 | 1.0 | 69.0 | 168 | 0.0 | 612 | 0.0 | 3 | 14 | 59 | 0.0 | 0.0 | 167 | 11.0 | 61 | 74 | 27 | 1 | |
| 4 | 2 | F | 293 | 82 | 0 | 3.0 | 77.0 | 180 | 1.0 | 612 | 0.0 | 2 | 9 | 61 | 9.0 | 0.0 | 262 | 15.0 | 60 | 60 | 43 | 1 |
# Mapper between concatenated clusters and hierarchical clusters
cluster_mapper = kmeans_clusters['hclust_labels'].to_dict()
df_ = df_concat.copy()
# Mapping the hierarchical clusters on the centroids to the observations
df_['merged_labels'] = df_.apply(
lambda row: cluster_mapper[
(row['Cluster'])
], axis=1
)
# Merged cluster centroids
df_.groupby('Cluster').mean().T
| Cluster | 0 | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|---|
| RFA_2F | 1.895010 | 1.894850 | 1.810676 | 1.734504 | 2.363964 | 1.900046 |
| IC3 | 386.739469 | 348.579127 | 354.708730 | 517.003997 | 378.654539 | 372.906525 |
| HHD2 | 71.797667 | 69.118520 | 68.738060 | 81.653690 | 71.783186 | 73.445627 |
| ETHC3 | 17.505768 | 20.131617 | 17.530343 | 10.694937 | 17.048553 | 17.728829 |
| INCOME | 3.821257 | 3.388881 | 3.746128 | 5.087765 | 3.780330 | 3.676076 |
| AGE | 59.749190 | 65.303547 | 56.209017 | 51.196153 | 59.247734 | 61.849607 |
| N_ODATEDW | 113.251458 | 151.997067 | 76.040343 | 111.104855 | 112.115237 | 125.219806 |
| NUMCHLD | 0.168373 | 0.072237 | 0.137165 | 0.529487 | 0.192972 | 0.257288 |
| N_RDATE_7 | 612.000000 | 612.000000 | 612.000000 | 612.000000 | 58.100211 | 557.402129 |
| RAMNT_7 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 15.528080 | 1.465988 |
| FEDGOV | 3.047440 | 2.719134 | 2.949983 | 4.004866 | 3.006830 | 3.155484 |
| VIETVETS | 29.701620 | 26.379025 | 27.722343 | 39.428861 | 29.783807 | 30.317446 |
| N_ADATE_7 | 612.000000 | 59.117156 | 59.128179 | 59.560364 | 59.409661 | 105.622397 |
| MBBOOKS | 0.412054 | 0.492599 | 0.351459 | 0.571544 | 0.430274 | 2.495604 |
| MBGARDEN | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 1.106432 |
| N_FISTDATE | 109.533247 | 144.871419 | 75.779664 | 107.681265 | 108.312058 | 120.300787 |
| MAXRAMNT | 19.186434 | 20.337427 | 19.669591 | 22.087804 | 18.179142 | 18.670292 |
| N_LASTDATE | 60.160207 | 61.745771 | 61.727314 | 62.684046 | 57.803303 | 61.226284 |
| N_MAXRDATE | 72.382631 | 83.558595 | 64.400826 | 71.736010 | 72.558053 | 75.725590 |
| CARDPROM | 16.252625 | 25.956548 | 10.617300 | 18.288669 | 17.682975 | 20.259602 |
| merged_labels | 1.000000 | 0.000000 | 1.000000 | 1.000000 | 0.000000 | 0.000000 |
df_.groupby('Cluster')['RFA_2A','PETS'].agg(pd.Series.mode).T
| Cluster | 0 | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|---|
| RFA_2A | F | F | F | F | F | F |
| PETS |
# Getting size of each final cluster
df_counts = df_.groupby('Cluster').size().to_frame()
df_counts
| 0 | |
|---|---|
| Cluster | |
| 0 | 7715 |
| 1 | 29320 |
| 2 | 26151 |
| 3 | 17262 |
| 4 | 8053 |
| 5 | 2161 |
Cluster 0 - Middle Class Donors
This is a medium-sized cluster - 7715 respondents. They were not received promotion 96G1 (Date the 96G1 promotion was mailed is maximum). They have practically the largest personal income; donations occur quite often (RFA_2F) and Dollar amount of largest gift to date was in 4th place out of 6. For most clustering variables, this cluster is close to the central values. As a variant of a possible strategy, it is recommended to test the 96G1 campaign on them as a typical one according to the dataset sample to assess the response and the strategy for further communication according to the results obtained.
Cluster 1 - Donations are Less Often than Average, Above Average
Majority (donations are less than average, above average) maximum cluster - 29,320 donors. Donors of this cluster are the most experienced donors - they have the earliest date of the first donation, the maximum amount of CARDPROM. This is the oldest group (65.30) with the maximum Percent White Age 60+ among the neighbors. At the same time, they have the lowest personal income among other clusters and practically have no children. They donate not very often (RFA_2F 4th out of 6), but in large amounts (MAXRAMNT 2nd out of 6). To maximize the income for mailings for this cluster due to its significant volume, it is recommended to work on the percentage of responses, increasing the frequency, even though this may lead to a decrease in the size of the average donation because of the effect of volume, the total income from this cluster will increase.
Cluster 2 - New Donors
This is the second-largest cluster with 26,151 donors. The date of the donor's first gift is minimal - these are new donors who also received some CARDPROM. At the same time, they have a low Percent of Households w / Families and Buy Books (they do not work with book mailings). Since they have an average Dollar amount of largest gift to date and, at the same time, the Frequency code for RFA_2 is rather rare (5 out of 6), you need to work on the frequency of communication with them, using information that they are new - tell more about the organization and its needs, involving them in the active life of the foundation, taking into account the demographic characteristics of the cluster.
Cluster 3 - Young, Rare but Large Donors
This is an important 17262-donor cluster. This cluster has a maximum Average Household Income in hundreds and HOUSEHOLD INCOME, as well as the highest NUMBER OF CHILDREN and % Employed by Fed Gov, % Vietnam Vets, and Percent Households with Families. They also have a maximum Dollar amount of largest gift to date, but a minimum Frequency code for RFA_2. As for recommendations for interaction with this cluster, local charitable family events are recommended in favor of the organization in assistance with the federal government (due to the high % Employed by Fed Gov) with the emphasis is on donation size.
Cluster 4 - Frequent Small Donations
This is a cluster of 8053 donors. This is the only cluster that performs well in the 96G1 mailing list. They have the maximum Frequency code for RFA_2, but the minimum Dollar amount of largest gift to date. The last donation was also closer to all other clusters (Date associated with the most recent gift). As a communication strategy with this cluster, attention should be paid to the maximizing donation sizes while maintaining donor loyalty (for example, using the success of the 96G1 campaign or indicating the need to replenish the fund for a certain amount for a limited period for a specific purpose).
Cluster 5 - Respondents to Other Types of Mail Orders
The smallest cluster is 2161 donors. These donors are characterized by a high percentage of participation in the Buy Books and Buy Gardening mailings. They have an average personal income and small but fairly stable donations. As a strategy, it is recommended to maximize donations with books or garden supplies, such as cross-promotion with book coupons in exchange for a donation.